Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures

D
DELTA
2002
The First IEEE International Workshop on Electronic Design, Test and Applications (DELTA '02)
Abstract - Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures

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The First IEEE International Workshop on Electronic Design, Test and Applications (DELTA '02)

Christchurch, New Zealand

January 29-January 31

ISBN: 0-7695-1453-7

	ASCII Text	x
	Florent Carlier, Fabienne Nouvel, Jacques Citerne, "Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures," Electronic Design, Test and Applications, IEEE International Workshop on, pp. 52, The First IEEE International Workshop on Electronic Design, Test and Applications (DELTA '02), 2002.

	BibTex	x
	@article{ 10.1109/DELTA.2002.994588, author = {Florent Carlier and Fabienne Nouvel and Jacques Citerne}, title = {Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures}, journal ={Electronic Design, Test and Applications, IEEE International Workshop on}, volume = {0}, year = {2002}, isbn = {0-7695-1453-7}, pages = {52}, doi = {http://doi.ieeecomputersociety.org/10.1109/DELTA.2002.994588}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Electronic Design, Test and Applications, IEEE International Workshop on TI - Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures SN - 0-7695-1453-7 SP EP A1 - Florent Carlier, A1 - Fabienne Nouvel, A1 - Jacques Citerne, PY - 2002 KW - NEURAL NETWORK KW - MULTI-USER DETECTION KW - GROWING GRID KW - KOHONEN KW - CDMA VL - 0 JA - Electronic Design, Test and Applications, IEEE International Workshop on ER -

Florent Carlier, INSA / LCST

Fabienne Nouvel, INSA / LCST

Jacques Citerne, INSA / LCST

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DELTA.2002.994588

In the upcoming high transmission rate system, based on code division multiple access, standard multi-user detection methods are restricted because of performance and implementation complexity issues. To end up with this issue, self-organized neural networks are proposed. An optimal multi-user detector can be implemented, by using Growing Grid network.

Index Terms:

NEURAL NETWORK, MULTI-USER DETECTION, GROWING GRID, KOHONEN, CDMA

Citation:

Florent Carlier, Fabienne Nouvel, Jacques Citerne, "Multi-User Detection for CDMA Communications Based on Self Organized Neural Networks Structures," delta, pp.52, The First IEEE International Workshop on Electronic Design, Test and Applications (DELTA '02), 2002

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