1,037 research outputs found
Turbo-Equalization Using Partial Gaussian Approximation
This paper deals with turbo-equalization for coded data transmission over
intersymbol interference (ISI) channels. We propose a message-passing algorithm
that uses the expectation-propagation rule to convert messages passed from the
demodulator-decoder to the equalizer and computes messages returned by the
equalizer by using a partial Gaussian approximation (PGA). Results from Monte
Carlo simulations show that this approach leads to a significant performance
improvement compared to state-of-the-art turbo-equalizers and allows for
trading performance with complexity. We exploit the specific structure of the
ISI channel model to significantly reduce the complexity of the PGA compared to
that considered in the initial paper proposing the method.Comment: 5 pages, 2 figures, submitted to IEEE Signal Processing Letters on 8
March, 201
A Low-Complexity Graph-Based LMMSE Receiver Designed for Colored Noise Induced by FTN-Signaling
We propose a low complexity graph-based linear minimum mean square error
(LMMSE) equalizer which considers both the intersymbol interference (ISI) and
the effect of non-white noise inherent in Faster-than-Nyquist (FTN) signaling.
In order to incorporate the statistics of noise signal into the factor graph
over which the LMMSE algorithm is implemented, we suggest a method that models
it as an autoregressive (AR) process. Furthermore, we develop a new mechanism
for exchange of information between the proposed equalizer and the channel
decoder through turbo iterations. Based on these improvements, we show that the
proposed low complexity receiver structure performs close to the optimal
decoder operating in ISI-free ideal scenario without FTN signaling through
simulations.Comment: 6 pages, 6 figures, IEEE Wireless Communications and Networking
Conference 2014, Istanbul, Turke
PAPR Constrained Power Allocation for Iterative Frequency Domain Multiuser SIMO Detector
Peak to average power ratio (PAPR) constrained power allocation in single
carrier multiuser (MU) single-input multiple-output (SIMO) systems with
iterative frequency domain (FD) soft cancelation (SC) minimum mean squared
error (MMSE) equalization is considered in this paper. To obtain full benefit
of the iterative receiver, its convergence properties need to be taken into
account also at the transmitter side. In this paper, we extend the existing
results on the area of convergence constrained power allocation (CCPA) to
consider the instantaneous PAPR at the transmit antenna of each user. In other
words, we will introduce a constraint that PAPR cannot exceed a predetermined
threshold. By adding the aforementioned constraint into the CCPA optimization
framework, the power efficiency of a power amplifier (PA) can be significantly
enhanced by enabling it to operate on its linear operation range. Hence, PAPR
constraint is especially beneficial for power limited cell-edge users. In this
paper, we will derive the instantaneous PAPR constraint as a function of
transmit power allocation. Furthermore, successive convex approximation is
derived for the PAPR constrained problem. Numerical results show that the
proposed method can achieve the objectives described above.Comment: Presented in IEEE International Conference on Communications (ICC)
201
Asymptotic Analysis and Design of Iterative Receivers for Non Linear ISI Channels
International audienceIn this paper, iterative receiver analysis and design for non linear satellite channels is investigated. To do so, an EXtrinsic Information Transfer (EXIT) chart-based optimization is applied using two major assumptions: the equalizer outputs follow a Gaussian Mixture distribution since we use non-binary modulations and partial interleavers are used between the Low Density Parity Check (LDPC) code and the mapper. Achievable rates, performance and thresholds of the optimized receiver are analysed. The objective in fine is to answer the question: Is it worth optimizing an iterative receiver for non linear satellite channels
Iterative Decoding and Turbo Equalization: The Z-Crease Phenomenon
Iterative probabilistic inference, popularly dubbed the soft-iterative
paradigm, has found great use in a wide range of communication applications,
including turbo decoding and turbo equalization. The classic approach of
analyzing the iterative approach inevitably use the statistical and
information-theoretical tools that bear ensemble-average flavors. This paper
consider the per-block error rate performance, and analyzes it using nonlinear
dynamical theory. By modeling the iterative processor as a nonlinear dynamical
system, we report a universal "Z-crease phenomenon:" the zig-zag or up-and-down
fluctuation -- rather than the monotonic decrease -- of the per-block errors,
as the number of iteration increases. Using the turbo decoder as an example, we
also report several interesting motion phenomenons which were not previously
reported, and which appear to correspond well with the notion of "pseudo
codewords" and "stopping/trapping sets." We further propose a heuristic
stopping criterion to control Z-crease and identify the best iteration. Our
stopping criterion is most useful for controlling the worst-case per-block
errors, and helps to significantly reduce the average-iteration numbers.Comment: 6 page
Turbo Decoding and Detection for Wireless Applications
A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted
An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels
In this paper, we introduce an efficient iterative solver for the joint
linear-programming (LP) decoding of low-density parity-check (LDPC) codes and
finite-state channels (FSCs). In particular, we extend the approach of
iterative approximate LP decoding, proposed by Vontobel and Koetter and
explored by Burshtein, to this problem. By taking advantage of the dual-domain
structure of the joint decoding LP, we obtain a convergent iterative algorithm
for joint LP decoding whose structure is similar to BCJR-based turbo
equalization (TE). The result is a joint iterative decoder whose complexity is
similar to TE but whose performance is similar to joint LP decoding. The main
advantage of this decoder is that it appears to provide the predictability of
joint LP decoding and superior performance with the computational complexity of
TE.Comment: To appear in Proc. IEEE ICC 2011, Kyoto, Japan, June 5-9, 201
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