Iterative decoding networks with iteratively data eliminating SDD and EM based channel state estimator
Jan Sykora,Alister G. Burr +1 more
- 05 Sep 2004
- Vol. 2, pp 785-790
TL;DR: A general framework for iterative separate CSE in general iterative decoding networks is established and two particular cases of CSE are examined - SDD and EM (expectation-maximization) based one.
read more
Abstract: The paper establishes a general framework for iterative separate CSE in general iterative decoding networks. Two particular cases of CSE are examined - SDD (soft-decision directed) and EM (expectation-maximization) based one. Both have capabilities for exploiting the iteratively improved backward measure from the decoding network, however both exhibit different properties and provide different possibilities for iteration scenarios. An example application with simple serially concatenated code with QPSK mapping in AWGN channel with phase rotation is investigated to demonstrate the differences between the algorithms in terms of MSE, ambiguity resolution, and convergence behavior.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Figures
![Fig. 5 Numerical results for (a) SDD and (b) EM CSE. The estimator objective function for different iterations and (1) successful ambiguity resolution, (2) synchronization failure. True channel phase is shown as a dashed line. The decoding loop iteration number is a parameter, γB = 2 [dB]. The MSE (3) as a function of the iteration number.](/figures/fig-5-numerical-results-for-a-sdd-and-b-em-cse-the-estimator-cgmhkdz9.png)
Fig. 5 Numerical results for (a) SDD and (b) EM CSE. The estimator objective function for different iterations and (1) successful ambiguity resolution, (2) synchronization failure. True channel phase is shown as a dashed line. The decoding loop iteration number is a parameter, γB = 2 [dB]. The MSE (3) as a function of the iteration number. 
Fig. 4 Probability of synchronization failure (ambiguity domain resolution). True channel phase is 80 degrees. 
Fig. 3 Iterative non-parametric EM decoding 
Fig. 1 PSISO module. 
Fig. 2 Iterative non-parametric SDD decoding
![Fig. 5 Numerical results for (a) SDD and (b) EM CSE. The estimator objective function for different iterations and (1) successful ambiguity resolution, (2) synchronization failure. True channel phase is shown as a dashed line. The decoding loop iteration number is a parameter, γB = 2 [dB]. The MSE (3) as a function of the iteration number.](/figures/fig-5-numerical-results-for-a-sdd-and-b-em-cse-the-estimator-cgmhkdz9.webp)
Citations
Iterative EM Based IMD Synchronization for Fast Time-Variant Channel with Subspace Order Recursive LS Iterator
Jan Sykora,Jan Vcelak +1 more
- 12 Dec 2005
TL;DR: This work solves the problem of iterative expectation-maximization (EM) based information measure directed (IMD) synchronization in fast time-variant environment by identifying correspondence between the EM iterator and the weighted least squares problem and an order recursive form of the LS iterator reduces the implementation complexity.
Subspace recursive weighted LS solution of iterative synchronisation in time-variant channel
Jan Sykora,Jan Vcelak +1 more
- 01 Oct 2008
TL;DR: The correspondence between the EM iterator and the weighted least squares (LS) problem is identified and a wide range of solutions developed for the LS problem are utilised including the subspace order recursive form of the LS iterator which reduces the implementation complexity.
2
New Negentropy Optimization Schemes for Blind Signal Extraction of Complex Valued Sources
TL;DR: A novel "reference-based" contrast function based on negentropy approximations is designed and a new family of algorithms is proposed to maximize it, and experiments for the separation of single sideband signals illustrate that the method has good prospects in real-world applications.
New Concept of PLC Modems: Multi-Carrier System for Frequency Selective Slow-Fading Channels Based on Layered SCCC Turbocodes
D. Kekrt,J. Zavrtalek,J. Hrad +2 more
TL;DR: A novel concept of a PLC modem as a complement to the existing G3 and PRIME standards for communications using mediumor high-voltage overhead or cable lines makes use of MCM, instead of OFDM, for lower latency and PAPR compared to OFDM.
Adaptive Subspace Iterative Information Measure Directed Synchronization in MIMO Channel
Jan Sykora,Jan Vcelak +1 more
- 11 Dec 2006
TL;DR: The paper addresses the problem of iterative soft-information measure supported synchronization with a subspace based model for the arbitrarily time-variant MIMO channel and introduces the idea of adaptive subspace control during the iterative synchronization iterations using the order recursive solver.
References
Fundamentals of statistical signal processing: estimation theory
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Near optimum error correcting coding and decoding: turbo-codes
Claude Berrou,A. Glavieux +1 more
TL;DR: A new family of convolutional codes, nicknamed turbo-codes, built from a particular concatenation of two recursive systematic codes, linked together by nonuniform interleaving appears to be close to the theoretical limit predicted by Shannon.