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Low-cost code-aided ML timing recovery from turbo-coded QAM transmissions
In this paper, we propose a new code-aided (CA) maximum likelihood (ML) approach for time synchronization in turbo-coded systems. The time delay estimate is refined at each turbo iteration owing to the increasingly accurate estimates for the log-likelihood ratios (LLRs) of the coded bits. The refine...
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Main Authors: | , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | In this paper, we propose a new code-aided (CA) maximum likelihood (ML) approach for time synchronization in turbo-coded systems. The time delay estimate is refined at each turbo iteration owing to the increasingly accurate estimates for the log-likelihood ratios (LLRs) of the coded bits. The refined time delay estimate is then used by the matched filter (MF) in order to provide the soft-input soft-output (SISO) decoders with more reliable symbol-rate samples for the next turbo iteration. Simulation results show the remarkable performance improvements of CA estimation against the traditional non-data-aided (NDA) estimation scheme. Moreover, the new CA ML estimator (MLE) enjoys significant advantage in computational complexity over existing ML CA solutions. |
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ISSN: | 2166-9589 |
DOI: | 10.1109/PIMRC.2017.8292608 |