DocumentCode :
2612333
Title :
A New Noise Variance Based Layered Pruning ML-DFE Algorithm
Author :
Ren, Shubo ; Mao, Xinyu ; Wu, Jianjun ; Xiang, Haige
Author_Institution :
Inst. of Modern Commun., Peking Univ., Beijing, China
fYear :
2012
fDate :
6-9 May 2012
Firstpage :
1
Lastpage :
4
Abstract :
A new noise variance based reduced maximum likelihood decision feedback equalization (ML-DFE) algorithm has been developed. This algorithm reduces the calculation complexity by exploring the intrinsic statistical properties layer by layer. Through setting layered thresholds, part of the nodes in the searching process will be cut by comparing with the thresholds. Simulation results show that the complexity drops lots while the performance drops small.
Keywords :
MIMO communication; communication complexity; decision feedback equalisers; maximum likelihood estimation; MIMO systems; intrinsic statistical properties; layered thresholds; noise variance-based layered pruning ML-DFE algorithm; noise variance-based reduced maximum likelihood decision feedback equalization algorithm; searching process; Algorithm design and analysis; Complexity theory; Decision feedback equalizers; MIMO; Maximum likelihood decoding; Maximum likelihood detection; Noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th
Conference_Location :
Yokohama
ISSN :
1550-2252
Print_ISBN :
978-1-4673-0989-9
Electronic_ISBN :
1550-2252
Type :
conf
DOI :
10.1109/VETECS.2012.6240120
Filename :
6240120
Link To Document :
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