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