Adaptive equalization

Qureshi, Shahzad Ahmad

doi:10.1109/mcom.1982.1090994

Cited by 199 publications

(113 citation statements)

References 7 publications

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“…Equation (4) illustrates that this key parameter decides a reliability dependent ratio between the no-noise amplitude of the received signal A, and the error correction calculation related parameter c. Especially in fading channels, L c varies continuously, this needs significantly less labor compared to varying c within a code block, which requires a lot of normalization to be performed in the metric computations. Essentially, the value of L c determines the relative amount of error correction involved in each transform operation in the Log-MAP decoding.…”

Section: Analysis Of the Channel Estimation Based On The Max-log-map mentioning

confidence: 99%

“…The channel estimator is a replica of the equivalent discrete time channel filter that models the ISI. The channel estimation is based on the known training sequence of bits that is repeated in every transmission burst [3][4][5]. A simple channel estimation algorithm for wireless system was firstly proposed in [6], using observations associated with orthogonal pilot symbols.…”

Section: Introductionmentioning

confidence: 99%

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A channel detection technique based on Max-Log-MAP algorithm for wireless indoor system

Kahveci

2010

Telecommun Syst

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This study introduces a new low complexity MaxLog-MAP based channel estimation technique operating in a multi-path band limited channel. The proposed estimation technique is based on an iterative procedure derived through the maximum a posteriori probability approach. Wireless communication channels often undergo frequency selective fading that leads to inter-symbol interference, which limits the performance of wireless indoor systems. Performance of the algorithms is assessed by combined analysis and simulation. Results are presented and compared against the performance of conventional Log-MAP algorithm. The obtained results show that the required bit-error-rate performance can be achieved with a lower number of iterations using the proposed low complexity algorithm compared to using the conventional Log-MAP algorithm.

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Section: Analysis Of the Channel Estimation Based On The Max-log-map mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A channel detection technique based on Max-Log-MAP algorithm for wireless indoor system

Kahveci

2010

Telecommun Syst

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“…Therefore, some equalization schemes are needed to compensate for these distortions at the receiving end, otherwise these distortions would result in high BER and even make the system unable to work [1,2] . Researches show that nonlinear equalization techniques should be adopted to availably mitigate distortions when the channel introduces severe nonlinear distortions [2,3] . During the past decades, various nonlinear equalizers have been proposed and developed.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these problems, two novel nonlinear adaptive equalizers are proposed in this paper based on the decision feedback architecture [3] and the Laguerre filter characteristic [15−18] , namely SNNDFE and LSNN equalizers. Both performance analysis and computer simulation show that the LSNN equalizer is not only stable, but also has better performance than others in eliminating various nonlinear distortions.…”

Section: Introductionmentioning

confidence: 99%

Neural FIR adaptive Laguerre equalizer with a gradient adaptive amplitude for nonlinear channel in communication systems

Zhao

Zhang

2009

Sci. China Ser. F-Inf. Sci.

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To mitigate the linear and nonlinear distortions in communication systems, two novel nonlinear adaptive equalizers are proposed on the basis of the neural finite impulse response (FIR) filter, decision feedback architecture and the characteristic of the Laguerre filter. They are neural FIR adaptive decision feedback equalizer (SNNDFE) and neural FIR adaptive Laguerre equalizer (LSNN). Of these two equalizers, the latter is simple and with characteristics of both infinite impulse response (IIR) and FIR filters; it can use shorter memory length to obtain better performance. As confirmed by theoretical analysis, the novel LSNN equalizer is stable (0

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“…(3) (4) (5) of lower values of the parameters is beneficial for establishment of the share of past observations. Therefore, determination of the parameters requires a careful approach since it necessarily involves a trade-off regarding the compensation of either the magnitude of fluctuations or the noise power.…”

Section: Introduction Of Differentialmentioning

confidence: 99%

Adaptive DFE control with differential LMS algorithm

Hoshino

Ohgane

Ogawa

2000

Electron. Comm. Jpn. Pt. I

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In order to implement high‐speed, high‐quality land‐mobile digital communications, it is necessary to simultaneously satisfy both the trackability of the frequency‐selectivity fading and the simplification of the algorithm. In this study, we propose the use of the differential LMS algorithm, which is applied to the decision feedback equalizer (DFE) as the adaptive algorithm. It can be expected that the introduction of the differential algorithm will make it possible to upgrade the tracking of propagation channels that can be approximated by the simplified Markov process. By using this algorithm, we designed an LMS‐DFE having a simple configuration, and evaluation of the propagation characteristics by computer simulation has shown that, compared to the conventional LMS‐DFE, it has better robustness to fluctuations and makes it possible to reduce the error floor by half. In addition, we also examined a diversity combined DFE and obtained similar results. © 2000 Scripta Technica, Electron Comm Jpn Pt 1, 84(1): 99–108, 2001

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Adaptive equalization

Cited by 199 publications

References 7 publications

A channel detection technique based on Max-Log-MAP algorithm for wireless indoor system

A channel detection technique based on Max-Log-MAP algorithm for wireless indoor system

Neural FIR adaptive Laguerre equalizer with a gradient adaptive amplitude for nonlinear channel in communication systems

Adaptive DFE control with differential LMS algorithm

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