2010 IEEE International Conference on Communications 2010
DOI: 10.1109/icc.2010.5502813
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A New Grouping-ML Detector with Low Complexity for SC-FDMA Systems

Abstract: In this paper, we propose a new grouping-maximum likelihood detector (GMLD) for single carrier-frequency division multiple access (SC-FDMA) systems. The proposed detector performs local maximum likelihood (ML) detection by grouping the received symbol block based on orthogonal projection to reduce the complexity of ML detector. As a result, the proposed detector offers lower complexity than the ML detector, while its performance approaches that of the ML detector. In addition, the efficient group size to guara… Show more

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Cited by 6 publications
(6 citation statements)
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“…After that, the detected symbol,ŝ Q 2 −i+1 , is extracted from (6), s Q 2 +i is detected using ML detection [7]. When s Q 2 −i+1 and s Q 2 +i are detected using ML detection at ith iteration, M candidates are selected in ascending order of their ED out of the total C candidate symbols (M ≤ C), which is called M -algorithm [10].…”
Section: Projection Of Bymentioning
confidence: 99%
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“…After that, the detected symbol,ŝ Q 2 −i+1 , is extracted from (6), s Q 2 +i is detected using ML detection [7]. When s Q 2 −i+1 and s Q 2 +i are detected using ML detection at ith iteration, M candidates are selected in ascending order of their ED out of the total C candidate symbols (M ≤ C), which is called M -algorithm [10].…”
Section: Projection Of Bymentioning
confidence: 99%
“…When s Q 2 −i+1 and s Q 2 +i are detected using ML detection at ith iteration, M candidates are selected in ascending order of their ED out of the total C candidate symbols (M ≤ C), which is called M -algorithm [10]. It can enhance the BER performance [7].…”
Section: Projection Of Bymentioning
confidence: 99%
See 3 more Smart Citations