Reduced-state sequence estimation with set partitioning and decision feedback

Eyüboğlu, Murat; Qureshi, Shahzad Ahmad

doi:10.1109/26.2724

Cited by 605 publications

(265 citation statements)

References 15 publications

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“…The number of trellis states of JRSSE-M is given by [13]. To distinguish between different partitionings, we characterize them by the number of used subsets: For DDFSE which may be seen as a special case of RSSE we have L κ ∈ {1, 8} for 8PSK.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In the worst case, only a single hypothesis with respect to the desired user signal may be held in memory and error propagation deteriorates performance. In this paper, we solve this problem by using the breadth-first sequential search algorithm (SA) [2], which may be interpreted as a combination of RSSE [13] and the M-algorithm. The considered states are defined according to an Ungerboeck set-partitioning, and a number of M paths is selected and stored for each state ν.…”

Section: Introductionmentioning

confidence: 99%

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Cochannel interference cancellation using optimized joint equalization

Nickel

Gerstacker

Koch

2007

2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications

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Abstract-In this paper, single-carrier transmission impaired by cochannel interference is considered, which generally arises in a GSM/ EDGE mobile radio network. Here, cochannel interference is created due to the reuse of the frequencies in nearby cells. In the case, that only a single antenna is available at the mobile receiver, the (multiple-input single-output) system is overloaded and equalization with low complexity is difficult. The optimum joint maximum-likelihood sequence estimation (JMLSE) algorithm would require a huge number of channel states to be considered in a corresponding Viterbi algorithm. The usage of a channel shortening filter in combination with a joint M-algorithm for detection was proposed in [1] in order to obtain good performance results at low complexity for singleantenna interference cancellation (SAIC) in the low-to-moderate carrier-to-interference power ratio (CIR) range, but unfortunately the M-algorithm has shown worse performance than joint delayed-decision feedback sequence estimation (JDDFSE) or joint reduced-state sequence estimation (JRSSE) for high CIRs. To solve this problem, we consider a combined scheme of JRSSE and the M-algorithm for joint detection of the desired user signal and one or more interferers, which corresponds to a special application of breadth-first sequence detection [2]. For the considered algorithm, each trellis state ν is equipped with a list of M (best) paths to be stored and processed forward.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cochannel interference cancellation using optimized joint equalization

Nickel

Gerstacker

Koch

2007

2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications

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“…Two of the more well known techniques are reduced state sequence estimation [EQ88] and delayed decision feedback estimation [DHH89]. Tree-search algorithms can be partitioned into optimal and suboptimal approaches.…”

Section: Decision Feedback Equalizationmentioning

confidence: 99%

Equalization of Time-Varying Channels

Schniter

Hwang

Das

et al. 2011

Wireless Communications Over Rapidly Time-Varying Channels

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“…Another more sophisticated algorithm is the reduced-state sequence estimation (RSSE), suggested by Eyuboglu and Qureshi [21]. Trellis states as defined in VA are merged using Ungerboeck-like set partitioning principles resulting in a simpler trellis.…”

Section: Suboptimal Viterbi-like Algorithmsmentioning

confidence: 99%

“…The complexity of VA increases rapidly with m and v, but hitherto most literatures focused on the effect of v. It seems that only a few researchers noticed that the complexity can be large for large m, even when v is very small [21]. In fact, the effect of m should deserve a lot of attention, as the effect of ISI in multilevel system is more noticeable [60].…”

Section: Trends Of Digital Transmission and Mlsementioning

confidence: 99%

Maximum likelihood sequence estimation from the lattice viewpoint

Mow

1992

[Proceedings] Singapore ICCS/ISITA `92

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Dedicated to my mother and the memory of my father ii Acknowledgement I would like to acknowledge my supervisor, Dr. C. P. Kwong, who introduced me the sequence estimation problem and encouraged me to look at it from new viewpoints. It is also him who taught me the right attitude, which I believe every true researcher ought to have, towards a difficult problem.iii Abstract It is well-known that the use of the Viterbi algorithm to implement a sequence estimator is an optimal way to remove the effect of intersymbol interference for digital transmission systems. However, such an implementation usually results in a very complicated receiver. In this thesis, we transform the problem of maximum likelihood sequence estimation into the problem of finding the closest lattice point. Some related lattice algorithms such as the basis reduction algorithms and the enumeration algorithms are analyzed and some improved versions are suggested. Then efficient algorithms finding the nearest lattice point are derived. Based on these lattice algorithms, simple but effective sequence estimators are proposed for the PAM systems and their complexities are analyzed. Under some mild assumptions, our algorithms have both polynomial space and time complexities, and are therefore much superior to the conventional Viterbi detectors. Simulation results on three different channels show that the performance of the new sequence estimators depend on the distance spectrum of the channel. But, general speaking, the performance approaches optimal as the size of the signal set and the signal-to-noise ratio increase. Finally, the extensions to other lattice-type modulation schemes and the impacts of the lattice viewpoint on the design of bandlimited transmission systems are discussed.iv

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Reduced-state sequence estimation with set partitioning and decision feedback

Cited by 605 publications

References 15 publications

Cochannel interference cancellation using optimized joint equalization

Cochannel interference cancellation using optimized joint equalization

Equalization of Time-Varying Channels

Maximum likelihood sequence estimation from the lattice viewpoint

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