Turbo-detection: a new approach to combat channel frequency selectivity

Picart, Annie; Didier, Pierre; Glavieux, Alain

doi:10.1109/icc.1997.595038

Cited by 34 publications

(16 citation statements)

References 3 publications

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“…This suggests that the MLSE approach, which directly relies on the subchannel impulse response, could be much better, but its exponential increase in complexity with respect to the impulse response length presents a big disadvantage, so that it can be prohibitive for practical implementation. On the other hand, the invention of the Turbo codes by Claude Berrou at al., [10], and the iterative algorithms [11] started to be used to implement the Turbo equalization or Turbo interferences cancellation [12], with just linear complexity with respect to the channel impulse response lengths. Whatsoever, the concatenation of the soft successive self-interference cancellation and channel decoding procedure in Turbo mode, [13], offers additional enhancement of the overall performance.…”

Section: Development Of the Coded Orthogonal Frequency Division Multimentioning

confidence: 99%

Interference cancellation in coded OFDM/OQAM

Aoude

Vallet

Nedic

2012

2012 International Symposium on Wireless Communication Systems (ISWCS)

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This paper addresses the concatenation of a convolutional code and COFDM/OQAM modulation transmitted over a time-dispersive radio channel. The proposed receiver is composed of a suitable OFDM/OQAM filter-bank demodulator, followed by an intersymbol and inter(-subchannel) interferences canceller and a SISO (Soft Input -Soft Output) decoder put in Turbo-like mode. The iterative algorithms are based on message passing on bipartite graphs. As an example, performance comparison with the linear subchannel equalization is presented.

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Section: Development Of the Coded Orthogonal Frequency Division Multimentioning

confidence: 99%

Interference cancellation in coded OFDM/OQAM

Aoude

Vallet

Nedic

2012

2012 International Symposium on Wireless Communication Systems (ISWCS)

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“…At each iteration, the equalizer and the decoder compute a posteriori probabilities (APPs) and extrinsic probabilities on the coded bits [7]. They exchange the extrinsic probabilities which will be used as a priori probabilities to improve iteratively their performance.…”

Section: Iterative Soft Channel Estimationmentioning

confidence: 99%

Optimal training sequence length for soft iterative channel estimation

Hadj‐Kacem¹,

Sellami²,

Kamoun³

2009

2009 16th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2009)

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In this paper, we consider the problem of optimization of the training sequence length when a turbo-detector composed of a maximum a posteriori (MAP) equalizer and a MAP decoder is used. The initial channel estimate based on the training sequence is iteratively improved using the Expectation Maximization (EM) algorithm. In order to "unbias" the EM estimates, a modified version of the EM estimator is used. The optimal length of the training sequence is found by maximizing an effective Signal-to-Noise Ratio (SNR) taking into account the data throughput loss due to the use of pilot symbols.

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“…The soft outputs produced by each decoder are passed to the other decoder where they serve as a priori information after removal of information already processed at earlier iterations, so that only the so-called extrinsic (new) information is processed at each iteration. This structure was later extended to QPSK signals [10] and SISO modules employing the MAP update rule were used in a mobile communicationscontext in [11]. Due to the bandwidth and coding gain efficiency of trellis-coded modulation (TCM) for frequency selective channels, some effort has also focused recently on the development of turbo equalizers for TCM signals.…”

Section: Introductionmentioning

confidence: 99%

Turbo Space–Time Equalization of TCM for Broadband Wireless Channels

Koca

Levy

2004

IEEE Trans. Wireless Commun.

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This paper presents a space-time turbo (iterative) equalization method for trellis-coded modulation (TCM) signals over broadband wireless channels. For fixed wireless systems operating at high data rates, the multipath delay spread becomes large, making it impossible to apply trellis-based equalization methods. The equalizer proposed here consists of a broadband beamformer which processes antenna array measurements to shorten the observed channel impulse response, followed by a conventional scalar turbo equalizer. Since the applicability of trellis-based equalizers is limited to additive white noise channels, the beamformer is required to preserve the whiteness of the noise at its output. This constraint is equivalent to requiring that the finite-impulse response (FIR) beamforming filters must have a power complementarity property. The power complementarity property imposes nonnegative definite quadratic constraints on the beamforming filters, so the beamformer design is expressed as a constrained quadratic optimization problem. The composite channel impulse response at the beamformer output is shortened significantly, making it possible to use a turbo equalizer for the joint equalization and decoding of trellis modulated signals. The proposed receiver structure is simulated for two-dimensional TCM signals such as 8-PSK and 16-QAM and the results indicate that the use of antenna arrays with only two or three elements allows a large decrease in the channel signal-to-noise ratio needed to achieve a 10 4 bit-error rate.Index Terms-Broadband beamforming, power complementary filter banks, soft-output decoding, turbo equalization.

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Turbo-detection: a new approach to combat channel frequency selectivity

Cited by 34 publications

References 3 publications

Interference cancellation in coded OFDM/OQAM

Interference cancellation in coded OFDM/OQAM

Optimal training sequence length for soft iterative channel estimation

Turbo Space–Time Equalization of TCM for Broadband Wireless Channels

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