Noncoherent coded modulation

Raphaeli, D.

doi:10.1109/26.486610

Cited by 104 publications

(91 citation statements)

References 14 publications

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“…In order to improve the performance, an increasing trend for PUD systems is to use a sequence of symbols at each time instant and apply a ML estimator for the used symbol sequence (Leib & Pasupathy, 1988;Divsalar & Simon, 1990;Lodge & Moher, 1990;Leib & Pasupathy, 1991;Colavolpe & Raheli, 1999;Guo & Qiu, 2006;Tian & Yang, 2008). The performance of noncoherent sequence detectors, which have no access to the absolute signal phase information, has been shown to approach that of the corresponding coherent sequence detectors if the phase ambiguity problem is solved but at the cost of increasing the decoder complexity (Raphaeli, 1996).…”

Section: Multiple Symbol Sequence Detectionmentioning

confidence: 99%

Low Complexity Phase-Unaware Detectors Based on Estimator-Correlator Concept

Anttonen¹,

Mämmelä²,

Pasupathy³

2011

Ultra Wideband Communications: Novel Trends - System, Architecture and Implementation

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Section: Multiple Symbol Sequence Detectionmentioning

confidence: 99%

Low Complexity Phase-Unaware Detectors Based on Estimator-Correlator Concept

Anttonen¹,

Mämmelä²,

Pasupathy³

2011

Ultra Wideband Communications: Novel Trends - System, Architecture and Implementation

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“…In particular, the integer , originally introduced as the phase-memory parameter in [18], quantifies the amount of channel memory taken into account in the trellis diagram of the considered detection block. By defining (14) (15) (16) it follows that the soft output on the right-hand side of (3), generated by a TM algorithm, that is denoted by , can be written as (17) It is possible to show that the quantities and can be calculated via forward and backward recursions, respectively, as [14] (18) (19) At this point, we emphasize that once the memory truncation is performed in (13), the TM-FB algorithm runs on a finite trellis (defined by the states ). In other words, no additional tree pruning is required.…”

Section: B Tm Adaptive Fb Algorithmsmentioning

confidence: 99%

“…The pilot symbols can be inserted in several points of the encoder structure. Their insertion leads to schemes that are antirotational invariant [15] and, consequently, noncoherently noncatastrophic [16]; that is, the unknown phase rotation introduced by the channel does not lead to any catastrophic behavior.…”

mentioning

confidence: 99%

Adaptive Iterative Detection for the Phase-Uncertain Channel: Limited-Tree-Search Versus Truncated-Memory Detection

Ferrari

Anastasopoulos

Colavolpe

et al. 2004

IEEE Trans. Veh. Technol.

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Abstract-In this paper, we consider iterative detection over bandpass channels that introduce an unknown phase rotation in the transmitted signal. This work focuses on the comparison between two adaptive detection strategies for trellis-based coded modulation: limited-tree-search (LTS) detection, obtained by reducing a tree search to a limited trellis search, and truncated-memory (TM) detection, based on channel-memory truncation, which automatically leads to a trellis search. Both strategies are used to derive trellis-based forward-backward (FB) algorithms. A quantitative analysis based on simulations, with various coding and modulation schemes, is carried out to evaluate and compare the two approaches. The results show that the channel-phase dynamics should significantly influence the choice of the detection strategy: For low-phase variations, LTS algorithms are a simple and reasonable choice, while for moderate to fast phase variations, TM algorithms show a considerable robustness.

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“…Using this property, we propose an efficient quantization scheme that maps points in the Grassmann manifold to points on a sphere that are appropriate for protection against channel effects. Specifically, we leverage existing trellis coded quantization (TCQ) technique for the noncoherent communication in our vector encoder [3]- [6]. This scheme enjoys efficient encoding and decoding with complexity linear to the total number of antennas, while providing decent performance.…”

Section: Introductionmentioning

confidence: 99%

Insights into feedback and feedback signaling for beamformer design

Au-Yeung

Jalali

Love

2009

2009 Information Theory and Applications Workshop

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Abstract-Multi-site cooperative transmission is gaining industrial support in latest standard development. One key criteria to sucessfully implement a multi-site cooperative transmission system is the need to quantize an expanded set of channels. To maintain quantization precision, codebook size needs to scale roughly exponentially with the number of total antennas and renders quantizing the expanded channel set a computationally demanding task. In this paper, we identify a connection between noncoherent communication and the phase invariant property of beamforming vectors. We leverage techniques from the noncoherent communication literature to design an efficient beamforming vector quantization scheme. Our proposed scheme has a quantization complexity that grows linearly with number of antennas. Simulation results indicate this method has slightly more quantization distortion than RVQ while being significantly more efficient.Index Terms-beamforming vector quantization, efficient vector quantization, trellis coded vector quantization

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Noncoherent coded modulation

Cited by 104 publications

References 14 publications

Low Complexity Phase-Unaware Detectors Based on Estimator-Correlator Concept

Low Complexity Phase-Unaware Detectors Based on Estimator-Correlator Concept

Adaptive Iterative Detection for the Phase-Uncertain Channel: Limited-Tree-Search Versus Truncated-Memory Detection

Insights into feedback and feedback signaling for beamformer design

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