An adaptive maximum-likelihood sequence estimator for fast time-varying intersymbol interference channels

Kubo, Hiroshi; Murakami, Keishi; Fujino, Tadashi

doi:10.1109/tcomm.1994.582897

Cited by 103 publications

(54 citation statements)

References 10 publications

(4 reference statements)

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“…The conventional adaptive MLSE receiver generally consists of an MLSE estimator implemented by the VA and a channel estimator which adaptively estimates the channel impulse response using the tentative decisions provided by VA as an estimate of the transmitted sequence [14], [15], [26]. The tentative decisions are obtained with a delay; if the delay is small, erroneous data decisions are given while a large delay causes a channel estimation delay decreasing the capability of tracking fast time-varying ISI channels [28]. Generally, the tentative decisions are made by truncating the survivor path history in the VA to some fixed length usually equal to ( indicates the memory length) giving a channel estimation delay.…”

Section: Adaptive Euclidean Distance Mlse Receiversmentioning

confidence: 99%

“…In the literature, two similar methods, the per-survivor method [7] and the channel estimation procedure proposed by Kubo et al [28], estimate the channel impulse response into the structure of the VA itself, along the survivor path connected to each state without the decision delay. In our method the channel estimation is made directly within the metric calculation of the VA with very restricted delay.…”

Section: Adaptive Euclidean Distance Mlse Receiversmentioning

confidence: 99%

“…The conventional adaptive MLSE receiver [3], [5] has difficulty in tracking fast time-varying ISI channels due to the fixed decision delay inherent in the VA which causes a channel estimation delay. In the literature [7], [28], the per-survivor processing (PPSP) and the adaptive MLSE proposed by Kubo et al are presented, which utilize data-aided estimation techniques within the VA without being influenced by the fixed decision delay. In these methods, the estimate of the channel impulse response is evaluated using the data sequence associated to each survivor path in the branch metric calculation, which is relative to a possible state transition in the Viterbi trellis.…”

Section: Introductionmentioning

confidence: 99%

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A continuously adaptive MLSE receiver for mobile communications: algorithm and performance

Castellini

Conti²,

et al. 1997

IEEE Trans. Commun.

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Abstract-The paper presents a Euclidean distance maximum likelihood sequence estimation (MLSE) receiver, based on the Viterbi algorithm (VA), suitable for fading and noisy communications channels, as that specified by the group spécial mobiles (GSM). In a mobile cellular system, the fast varying channel characteristics, due to the fading and Doppler effects, require adaptive methods to update the channel coefficients to the MLSE receiver. The proposed technique continuously estimates the channel characteristics directly within the metric calculation of the VA. At each step of the VA, the sequence associated to the path with the best metric value (minimum-survivor method) among the survivor paths is used to update the channel estimate (employing conventional adaptive algorithms) throughout the entire informative sequence. However, the detection of the transmitted data sequence is performed by the VA only at the end of each burst.The proposed technique allows simpler receiver implementation and the simulation results show a good performance of this adaptive MLSE receiver in typical GSM environments.

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Section: Adaptive Euclidean Distance Mlse Receiversmentioning

confidence: 99%

Section: Adaptive Euclidean Distance Mlse Receiversmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A continuously adaptive MLSE receiver for mobile communications: algorithm and performance

Castellini

Conti²,

et al. 1997

IEEE Trans. Commun.

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“…For example, Kubo, Murakami, and Fujino [KMF94] proposed to use the Viterbi algorithm in conjunction with the LMS algorithm [Hay01] for per-survivor channel estimation, whereas Raheli, Polydoros, and Tzou [RPT95] proposed to use the Viterbi algorithm in conjunction with the RLS algorithm [Hay01]. Other LMS and RLS approaches were discussed in [AC00].…”

Section: Reduced-complexity Trellis-psp Equalization For Single-carrimentioning

confidence: 99%

Equalization of Time-Varying Channels

Schniter

Hwang

Das

et al. 2011

Wireless Communications Over Rapidly Time-Varying Channels

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“…The authors have investigated per-transmit antenna differential mapping (PADM), which is one of the DSTTCs [12], [13]. The demodulation scheme of PADM requires per-survivor processing (PSP) [14]- [16] based on the Viterbi algorithm (VA). In addition, PADM can be applied not only to transmit diversity but also to spatial multiplexing.…”

Section: Introductionmentioning

confidence: 99%

Differential MIMO Spatial Multiplexing Employing PADM Based on Channel Prediction for Fast Time-Varying Channels

Mori

Takuma

Akinobu

et al. 2017

Journal of Signal Processing

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This paper proposes a demodulation scheme based on channel prediction for differential multiple-input multipleoutput (MIMO) spatial multiplexing employing per-transmit antenna differential mapping (PADM). As PADM is one of the differential space-time trellis codings (DSTTCs), it requires per-survivor processing (PSP) based on the Viterbi algorithm (VA) for its demodulation. Therefore, PADM has excellent tracking performance on fast time-varying channels. However, aiming at higher frequency efficiency, PADM for a higher modulation index suffers from the following two disadvantages: (1) poor receiver sensitivity; (2) high computational complexity. In order to solve the items (1) and (2), this paper employs a spatial multiplexing structure and a state reduction algorithm for the VA, i.e., decision-feedback sequence estimation (DFSE), respectively. Finally, for a frequency efficiency of 4bps/Hz with two receive antennas, computer simulation results confirm that the proposed scheme has excellent bit error rate (BER) performance on fast time-varying channels in the case of the maximum Doppler frequency normalized by a symbol rate of 4%.

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An adaptive maximum-likelihood sequence estimator for fast time-varying intersymbol interference channels

Cited by 103 publications

References 10 publications

A continuously adaptive MLSE receiver for mobile communications: algorithm and performance

A continuously adaptive MLSE receiver for mobile communications: algorithm and performance

Equalization of Time-Varying Channels

Differential MIMO Spatial Multiplexing Employing PADM Based on Channel Prediction for Fast Time-Varying Channels

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