Adaptive receiver for data transmission over time-dispersive channels

Qureshi, Shahzad Ahmad; Newhall, E. E.

doi:10.1109/tit.1973.1055046

Cited by 144 publications

(49 citation statements)

References 14 publications

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“…The LMSAM scans the data for particular patterns and adapts the equalizer in order to minimize E[X 2 e ] for single-bit errors at data transitions. However, as storage capacity increases, other error events, e.g., the double-bit errors e = ±[1, 0, −1], become substantial.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…One can check that the matrix M e is positive and, therefore, the denominator increases when m = 0 compared to m = 0. e m e , whereas it has been shown that this sign is of capital importance for Pr(ACS error|e). We conclude that minimizing E[X 2 e ], as suggested in [7], is not optimal in general. Simulation results of Fig.…”

Section: A Impact Of Residual Isi On the Sequenced Amplitude Marginmentioning

confidence: 90%

“…A first attempt toward this goal is to minimize E[X 2 e ] according to the LMSAM algorithm, as suggested, for single-bit errors, in [7]. However, this is not optimal because minimization of E[X (4).…”

Section: Derivation Of the Adaptation Criterionmentioning

confidence: 99%

“…A Viterbi detector (VD), suitable for the target response [2], subsequently estimates the transmitted data sequence. Such systems are known as partial response maximumlikelihood (PRML) systems.…”

Section: Introductionmentioning

confidence: 99%

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Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

Riani

Beneden

Bergmans

et al. 2007

IEEE Trans. Commun.

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Abstract-Receivers for partial response maximum-likelihood systems typically use a linear equalizer followed by a Viterbi detector. The equalizer tries to confine the channel intersymbol interferenceto a short span in order to limit the implementation complexity of the Viterbi detector. Equalization is usually made adaptive in order to compensate for channel variations. Conventional adaptation techniques, e.g., LMS, are, in general, suboptimal in terms of bit-error rate (BER). In this paper, we present a new equalizer adaptation algorithm that seeks to minimize the BER at the Viterbi detector output. The algorithm extracts information from the sequenced amplitude margin (SAM) histogram and incorporates a selection mechanism that focuses adaptation on particular data and noise realizations. The selection mechanism is based on the reliability of the add compare select (ACS) operations in the Viterbi detector. From a complexity standpoint, the algorithm is essentially as simple as the conventional LMS algorithm. Moreover, we present a further simplified version of the algorithm that does not require any hardware multiplications. Simulation results, for an idealized optical storage channel, confirm a substantial performance improvement relative to existing adaptation algorithms.Index Terms-Adaptive equalizers, intersymbol interference, partial response signaling, sequenced amplitude margin (SAM), Viterbi detection.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: A Impact Of Residual Isi On the Sequenced Amplitude Marginmentioning

confidence: 90%

Section: Derivation Of the Adaptation Criterionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

Riani

Beneden

Bergmans

et al. 2007

IEEE Trans. Commun.

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“…A continuación se caracteriza analíticamente el ecualizador adaptativo [12] y [15]. Después del período de entrenamiento inicial los coeficientes de un ecualizador adaptativo se pueden ajustar continuadamente en una decisión de manera directa.…”

Section: Ecualizadores Adaptivosunclassified

Estudio del desempeño de la concatenación de ecualizador de baja complejidad con código NRZ-LDPC irregular para canales inalámbricos móviles

R¹,

P²

2014

Ingeniare. Rev. chil. ing.

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RESUMENSe estudia el desempeño de un sistema de comunicación para redes inalámbricas móviles basado en la concatenación de código no retorno a cero, código de chequeo de paridad de baja densidad irregular y ecualizador de dos bits. El transmisor se compone de un codificador de línea NRZ y un codificador LDPC con bajo umbral de error. El receptor se compone de un decodificador suma producto y un ecualizador que utiliza el algoritmo de estimación de secuencia de máxima probabilidad. El sistema de comunicación se simula sobre un canal con ruido aditivo blanco Gaussiano y desvanecimiento rápido con distribución Rayleigh, para diferentes tamaños de la palabra de código. La velocidad del móvil se considera igual a 150 km/h. El desempeño del sistema se determina en función de la probabilidad de error de bit y la razón señal a ruido, obteniendo para un BER de 10 -5 una SNR de 9 dB para el caso del codificador NRZ-LDPC sin ecualizador y una SNR de 4,5 dB para el caso del codificador NRZ-LDPC con ecualizador. Los resultados del estudio de desempeño indican que con el sistema formado por la concatenación de ecualizador con código NRZ-LDPC se logra una reducción apreciable de la SNR.Palabras clave: Código chequeo de paridad de baja densidad irregular, ecualizador, desvanecimiento rápido, redes inalámbricas, cuarta generación. ABSTRACT A communications system for mobile wireless networks based on concatenation of code NRZ, irregular LDPC code and equalizer of two bits is studied. The transmitter is composed of a NRZ line coder and irregular LDPC coder with a low error threshold. The receiver is composed of the sum-product decoder and

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2013

Wireless Communications

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Adaptive receiver for data transmission over time-dispersive channels

Cited by 144 publications

References 14 publications

Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

Estudio del desempeño de la concatenación de ecualizador de baja complejidad con código NRZ-LDPC irregular para canales inalámbricos móviles

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