2015
DOI: 10.1109/tvt.2014.2366195
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A reduced-complexity demapping algorithm for BICM-ID systems

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Cited by 10 publications
(8 citation statements)
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“…Hence, we focus on the calculation of the extrinsic LLR L e,dem in the MAP demodulator, which is directly related to complexity comparison for both two demapping schemes. For the standard MAP demodulator, the calculation of L e,dem in equation 7requires a complexity on the order of O(2 M ), since the channel conditional probability p(Y k |S k ) needs 2 M times Euclidean distance calculations for all the 2 M constellation points [30]. Moreover, the maximization operation involves 2 M − 2 comparisons, which is the same as that of the GMM-based demodulator.…”
Section: Complexity Analysismentioning
confidence: 99%
“…Hence, we focus on the calculation of the extrinsic LLR L e,dem in the MAP demodulator, which is directly related to complexity comparison for both two demapping schemes. For the standard MAP demodulator, the calculation of L e,dem in equation 7requires a complexity on the order of O(2 M ), since the channel conditional probability p(Y k |S k ) needs 2 M times Euclidean distance calculations for all the 2 M constellation points [30]. Moreover, the maximization operation involves 2 M − 2 comparisons, which is the same as that of the GMM-based demodulator.…”
Section: Complexity Analysismentioning
confidence: 99%
“…The complexity of the ML scheme can be reduced by eliminating the log and exponential operations, resulting in a scheme called Max-log soft demodulation, but this scheme still has exponential-order complexity. A number of soft demodulation schemes have been proposed to reduce the complexity [3][4][5][6][7][8][9][10][11][12][13][14][15]; these can be classified into three classes as follows.…”
Section: Introductionmentioning
confidence: 99%
“…The third class of soft demodulation schemes comprises those based on a modified Max method, which eliminates the searching process to find the symbol with the minimum distance among the 2 m symbols in the constellation [12][13][14][15][16]. These methods determine the location of its detected symbol by comparison with the HDT lines, thereby requiring only m comparisons to find the nearest symbol, i.e.…”
Section: Introductionmentioning
confidence: 99%
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