This paper considers the turbo equalization of trellis-coded modulated (TCM) broadband wireless signals that are affected by both intersymbol interference (ISI) due to multipath propagation and cochannel interference ...
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This paper considers the turbo equalization of trellis-coded modulated (TCM) broadband wireless signals that are affected by both intersymbol interference (ISI) due to multipath propagation and cochannel interference (CCI) due to the presence of adjacent users. Long channel dispersion causing both impediments to be severe makes the direct application of trellis-based turbo equalizers impossible, particularly for high-order signal modulations. For this reason, we present two computationally feasible space-time turbo receiver architectures employing linear antenna arrays and broadband beamformers. The first receiver uses a beamformer for joint rejection of interfering signals and shortening of the channel corresponding to the desired signal so that a scalar trellis-based turbo equalizer can be applied to its output. At each beamformer branch, the composite effect of the CCI and the white channel noise is viewed as colored noise. Because trellis search algorithms are limited to cases where the observation noise is white, this imposes quadratic noise whitening constraints on the beamfornier design that is solved by a Lagrangian relaxation approach. The second receiver architecture removes the dependence on trellis search techniques for equalization by implementing the turbo equalizer directly with a soft-information-aided broadband beamformer at its front end and a soft-input soft-output (SISO) decoder at its back end. We outline the design considerations associated with each receiver and present bit error rate (BER) simulations for the turbo equalization of 8-phase-shift keying (PSK) TCM signals.
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 multipat...
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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.
A soft-output Viterbi algorithm (SOVA) that can be used on trellis-coded modulation (TCM), rate-kin convolutional codes, and intersymbol interference (ISI) channels is proposed. The algorithm utilizes the postdetector...
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A soft-output Viterbi algorithm (SOVA) that can be used on trellis-coded modulation (TCM), rate-kin convolutional codes, and intersymbol interference (ISI) channels is proposed. The algorithm utilizes the postdetector architecture proposed by Berrou et nl, [6] to achieve low computational complexity. By starting with Battail's [4] generalized revision algorithm and rereferencing the "relative values" to the surviving path to each state, substantial simplifications are made possible. By comparing the revision operations dictated by the simplified revision equation for a rate-1/n convolutional code to the operations mandated by the rate-1/n postdetector algorithm presented by Berrou ef al,, it is possible to deduce the additional modifications necessary to produce a rate-k/n postdetector algorithm. Computer simulations suggest that the derived rate-k/n algorithm produces reasonably good a posteriori input probability estimates for rate-k/n convolutional codes and trellis codes. The algorithm may also be used for soft-output Viterbi equalization (SOVE) provided that the channel impairments are not too severe.
In this paper, an adaptive forwarding strategy for wireless networks with relays is introduced. The strategy evaluates the error probability of a received code word at a relay based on reliability information provided...
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In this paper, an adaptive forwarding strategy for wireless networks with relays is introduced. The strategy evaluates the error probability of a received code word at a relay based on reliability information provided by a soft-output detector. It allows to adapt to changing channel conditions by switching between the amplify and forward and the decode and forward strategy and thus may help to decrease energy consumption and delay at the relays.
A variant of the best-path (BP) algorithm that can be used for deducing a posteriori symbol probabilities for input sequences of unlimited length is proposed. Decoders using the proposed algorithm have fixed memory re...
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A variant of the best-path (BP) algorithm that can be used for deducing a posteriori symbol probabilities for input sequences of unlimited length is proposed. Decoders using the proposed algorithm have fixed memory requirements and fixed decoding delays regardless of the length of the transmitted sequence. This is made possible by utilizing the Viterbi algorithm's ability to self-initialize itself and by segmenting the decoding process.
Bit error probability (BEP) and word error probability (WEP) are used as reliability-based retransmission criteria in conjunction with hybrid ARQ (HARQ) protocols. Instead of exploiting an error-detecting code, the de...
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Bit error probability (BEP) and word error probability (WEP) are used as reliability-based retransmission criteria in conjunction with hybrid ARQ (HARQ) protocols. Instead of exploiting an error-detecting code, the decision for a retransmission is based on the error probability of the decoded word, which can be calculated in or after the decoding process.
A new type of recursive algorithm for decoding turbo codes is proposed, based on a symbol-by-symbol maximum a posteriori probability algorithm. It requires only a forward recursion and has lower computational complexi...
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A new type of recursive algorithm for decoding turbo codes is proposed, based on a symbol-by-symbol maximum a posteriori probability algorithm. It requires only a forward recursion and has lower computational complexity. The number of variables to be stored increases linearly with the decoding delay. For iterative decoding, the extrinsic information given by the new algorithm is also described. This algorithm can be used in continuous decoding for both recursive and non-recursive encoder.
After the rediscovery of low-density parity-check (LDPC) codes, their decoding algorithms have been studied by mathematical tools pertinent more to computer science than the conventional algebraic coding theory. We pr...
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A soft-output data-detection scheme optimized for data-dependent media-noise recording channels is proposed that uses signal-dependent correlation-sensitive (SDCS) metric estimation for post-processing decoding. This ...
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ISBN:
(纸本)0780379748
A soft-output data-detection scheme optimized for data-dependent media-noise recording channels is proposed that uses signal-dependent correlation-sensitive (SDCS) metric estimation for post-processing decoding. This media-noise soft-output (MNS) decoding scheme achieves sub-optimal maximum-likelihood (ML) sequence detection in a non-stationary media-noise channel, while still using traditional Viterbi detection. Because it drastically reduces SDCS metric computation by focusing on only specified dominant error-events in the ML detector, it is less complex than other sub-optimal detection schemes. Moreover, its one-shot post-processing scheme enables the use of a simple lookup-table architecture suitable for highspeed circuit implementation. Simulation showed that the MNS decoding scheme in conjunction with a conventional (MEPRML)-P-2 system provides an excellent tradeoff between data-detection performance and computation complexity for a media-noise-dominant high-density recording channel.
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