Adaptive soft-input soft-output algorithms for iterative detection with parametric uncertainty

Anastasopoulos, Achilleas; Chugg, K.M.

doi:10.1109/26.871389

Cited by 91 publications

(69 citation statements)

References 30 publications

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“…Also, incorporation of additional levels of error-correction coding using recent adaptive iterative detection techniques [27] is another promising research direction.…”

Section: Discussionmentioning

confidence: 99%

Combined Coding and Training for Unknown ISI Channels

Coskun

Chugg

2005

IEEE Trans. Commun.

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Abstract-The traditional method of sending a training signal to identify a channel, followed by data, may be viewed as a simple code for the unknown channel. Results in blind sequence detection suggest that performance similar to this traditional approach can be obtained without training. However, for short packets and/or time-recursive algorithms, significant error floors exist due to the presence of sequences that are indistinguishable without knowledge of the channel. In this paper, we reconsider training-signal design in light of recent results in blind sequence detection. Specifically, we consider the tradeoff between the complexity of receiver processing and the amount of training overhead required. More generally, we design training codes which combine modulation and training. In order to design these codes, we find an expression for the pairwise error probability of the joint maximum-likelihood (JML) channel and sequence estimator. This expression motivates a pairwise distance for the JML receiver based on principal angles between the range spaces of data matrices. The general code-design problem (generalized sphere packing) is formulated as the clique problem associated with an unweighted, undirected graph. We provide optimal and heuristic algorithms for this clique problem. For both long and short packets, we demonstrate that significant improvements are possible by jointly considering the design of the training, modulation, and receiver processing.

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“…Also, incorporation of additional levels of error-correction coding using recent adaptive iterative detection techniques [27] is another promising research direction.…”

Section: Discussionmentioning

confidence: 99%

Combined Coding and Training for Unknown ISI Channels

Coskun

Chugg

2005

IEEE Trans. Commun.

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“…Channel estimation is also considered in this paper. The bidirectional trellis based approaches that carry out channel estimation and equalization simultaneously [30]- [32] deliver good performance, but their computational complexities are often intractable. In this paper, we follow the more practical framework of iterative joint channel estimation and detection discussed in [10]- [13], [28], and [29], in which the channel estimator is separated out from the equalizer.…”

Section: A Low-complexity Iterative Channel Estimation and Detection mentioning

confidence: 99%

A Low-Complexity Iterative Channel Estimation and Detection Technique for Doubly Selective Channels

Guo

Ping

2008

IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference

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In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-prefixing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a low-complexity bidirectional channel estimator, where the Gaussian message passing (GMP) Abstract-In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-preſxing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a lowcomplexity bidirectional channel estimator, where the Gaussian message passing (GMP) technique is used to exploit the channel correlation information, and the intermediate channel estimation results in the iterative process are employed to perform intertap interference cancellation. Simulation results demonstrate the effectiveness of the proposed detection and channel estimation algorithms.

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“…The PSP-BCJR module can be considered as a special case of the so-called adaptive SISO module developed by Anastasopoulos and Chugg [11]. In [11], the exact expressions for the soft metrics in the presence of parametric uncertainty modeled as a Gauss-Markov process were derived, but the complexity is huge.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], the exact expressions for the soft metrics in the presence of parametric uncertainty modeled as a Gauss-Markov process were derived, but the complexity is huge. Suboptimal solutions have also been proposed in [11], and used in the trellis-coded modulation (TCM) in interleaved frequency-selective fading channels [11] and the turbo-coded systems with carrier phase tracking [12]. Nevertheless, the application of timing recovery for the intersymbol interference (ISI) channel with time-varying timing offsets has not been addressed and investigated.…”

Section: Introductionmentioning

confidence: 99%

Per-survivor iterative timing recovery for coded partial response channels

Kovintavewat

Barry

Erden³

et al.

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.

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Abstract-We propose a new iterative timing recovery scheme based on per-survivor processing that jointly performs timing recovery and turbo equalization on partial response channels with error-correction codes. The scheme embeds the timing recovery process inside the Bahl, Cocke, Jelinek, and Raviv (BCJR) equalizer using per-survivor processing. This per-survivor BCJR equalizer then iteratively exchanges soft information with an error-correction decoder. Results indicate that the proposed scheme yields a better performance than a conventional receiver that performs timing recovery and turbo equalization separately, and also the iterative timing recovery scheme proposed in [1], especially when the channel encounters severe timing jitter noise. We also present evidence that suggests that the proposed scheme can correct a cycle slip much more efficiently than the others.

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Adaptive soft-input soft-output algorithms for iterative detection with parametric uncertainty

Cited by 91 publications

References 30 publications

Combined Coding and Training for Unknown ISI Channels

Combined Coding and Training for Unknown ISI Channels

A Low-Complexity Iterative Channel Estimation and Detection Technique for Doubly Selective Channels

Per-survivor iterative timing recovery for coded partial response channels

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