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Abstract
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Article Information:
A Modified Nonparametric Message Passing Algorithm for Soft Iterative Channel Estimation
Linlin Duan, Zhongyong Wang, Xiangchuan Gao and Wei Wang
Corresponding Author: Linlin Duan
Submitted: December 28, 2012
Accepted: January 19, 2013
Published: August 20, 2013 |
Abstract:
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Based on the factor graph framework, we derived a Modified Nonparametric Message Passing Algorithm (MNMPA) for soft iterative channel estimation in a Low Density Parity-Check (LDPC) coded Bit-Interleaved Coded Modulation (BICM) system. The algorithm combines ideas from Particle Filtering (PF) with popular factor graph techniques. A Markov Chain Monte Carlo (MCMC) move step is added after typical sequential Important Sampling (SIS) -resampling to prevent particle impoverishment and to improve channel estimation precision. To reduce complexity, a new max-sum rule for updating particle based messages is reformulated and two proper update schedules are designed. Simulation results illustrate the effectiveness of MNMPA and its comparison with other sum-product algorithms in a Gaussian or non-Gaussian noise environment. We also studied the effect of the particle number, pilot symbol spacing and different schedules on BER performance.
Key words: Channel estimation, Markov Chain Monte Carlo (MCMC), max-sum rule, message passing algorithm, , ,
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Cite this Reference:
Linlin Duan, Zhongyong Wang, Xiangchuan Gao and Wei Wang, . A Modified Nonparametric Message Passing Algorithm for Soft Iterative Channel Estimation. Research Journal of Applied Sciences, Engineering and Technology, (15): 2764-2772.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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