A binary adaptive decision-selection equalizer for channels with nonlinear intersymbol interference

Sebald, D.J.; Bucklew, J.A.

doi:10.1109/tsp.2002.801913

Cited by 3 publications

(13 citation statements)

References 19 publications

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“…1, is similar to that of [2] with a minor change in the feedback portion of the system. This change is necessary for implementing the tree structured con cept, and it makes the statistics of the input to the ADFE and ADSE similar for sake of comparing convergence properties.…”

Section: System Modelmentioning

confidence: 57%

“…The input x( n) is fed into an adaptive, delay network with coefficients wk, -y ( n) E JR, k = 0, ... , Nw -1, while the past decisions, u( n -D), are fed back through another adaptive, de lay network with coefficients bk, -y ( n) E JR, k = 1, ... , Nb, where ,( n) E z: is the selection variable derived from the past decision state. Similar to what was done in [2], define vectors…”

Section: System Modelmentioning

confidence: 99%

“…Equalization strategies which condition on a detector's past decision state were studied in papers such as [1] and, more recently, [2] where the idea of the hyperplane-based ADSE for channels with nonlinear lSI was proposed. See [2] for references and discussion of the prob lem and historical solutions.…”

Section: Introductionmentioning

confidence: 99%

“…See [2] for references and discussion of the prob lem and historical solutions. Two notable open issues exist for the ADSE as proposed in [2]: slow convergence rate and the fact that the hyperplane optimiz ing the minimum mean-squared error (MMSE)-which the LMS, or stochastic gradient decent, algorithm attempts to achieve-does not necessarily equate to the minimum probability of error for the detec tor. The convergence speed of the LMS-based ADSE is considered in this correspondence.…”

Section: Introductionmentioning

confidence: 99%

“…The convergence speed of the LMS-based ADSE is considered in this correspondence. The algorithm to follow is an interesting generalization of the ADSE having a tree-structured approach to hy perplane models, for which it will be seen that the ADSE as pro posed in [2] and the conventional ADFE are simply single levels at either end of the hierarchy. Simulations show that the tree-structured ADSE (TSADSE) has robust convergence properties for the exam ple nonlinear channel studied here, and its speed of convergence is noticeably faster than that of the non-tree-structured ADSE.…”

Section: Introductionmentioning

confidence: 99%

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Fast adaptive decision-selection equalizer convergence using a tree-structured algorithm

Sebald¹

2012

2012 IEEE Statistical Signal Processing Workshop (SSP)

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Previous research on adaptive equalization indicates that for some communications channels with nonlinear intersymbol interference (lSI) the decision state conventionally used as feedback can instead be used to select a detector model in order to achieve improved per formance while maintaining simplicity compared to historic nonlin ear solutions. For example, one method studied enhances the famil iar adaptive decision feedback equalizer (ADFE) for binary trans mission by using the past decision state to choose and adapt differ ent sets of coefficients, i.e., different hyperplane detector boundaries.One notable drawback to the least-mean-squared (LMS) based adap tive decision-selection equalizer (ADSE) as implemented previously is decreased convergence rate. A tree-structured algorithm is pro posed herein to speed convergence when the various conditional hy perplanes are not orthogonal in exchange for a manageable increase in memory and processing.

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Section: System Modelmentioning

confidence: 57%

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fast adaptive decision-selection equalizer convergence using a tree-structured algorithm

Sebald¹

2012

2012 IEEE Statistical Signal Processing Workshop (SSP)

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Functional link equaliser with decision selection for combatting cochannel interference

Paterson

Soraghan

2005

IEEE/SP 13th Workshop on Statistical Signal Processing, 2005

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Joint Detection/Decoding Algorithms for Nonbinary LDPC Codes over ISI Channels

Zhao,

Lu,

et al. 2012

Preprint

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This paper is concerned with the application of nonbinary low-density parity-check (NB-LDPC) codes to binary input inter-symbol interference (ISI) channels. Two low-complexity joint detection/decoding algorithms are proposed. One is referred to as max-log-MAP/X-EMS algorithm, which is implemented by exchanging soft messages between the max-log-MAP detector and the extended min-sum (EMS) decoder. The max-log-MAP/X-EMS algorithm is applicable to general NB-LDPC codes. The other one, referred to as Viterbi/GMLGD algorithm, is designed in particular for majority-logic decodable NB-LDPC codes. The Viterbi/GMLGD algorithm works in an iterative manner by exchanging harddecisions between the Viterbi detector and the generalized majority-logic decoder (GMLGD). As a byproduct, a variant of the original EMS algorithm is proposed, which is referred to as µ-EMS algorithm.In the µ-EMS algorithm, the messages are truncated according to an adaptive threshold, resulting in a more efficient algorithm. Simulations results show that the max-log-MAP/X-EMS algorithm performs as well as the traditional iterative detection/decoding algorithm based on the BCJR algorithm and the QSPA, but with lower complexity. The complexity can be further reduced for majority-logic decodable NB-LDPC codes by executing the Viterbi/GMLGD algorithm with a performance degradation within one dB. Simulation results also confirm that the µ-EMS algorithm requires lower computational loads than the EMS algorithm with a fixed threshold. These algorithms provide good candidates for trade-offs between performance and complexity.

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A binary adaptive decision-selection equalizer for channels with nonlinear intersymbol interference

Cited by 3 publications

References 19 publications

Fast adaptive decision-selection equalizer convergence using a tree-structured algorithm

Fast adaptive decision-selection equalizer convergence using a tree-structured algorithm

Functional link equaliser with decision selection for combatting cochannel interference

Joint Detection/Decoding Algorithms for Nonbinary LDPC Codes over ISI Channels

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