NDLI: Architecture Of A Neural Processor For Fourth Generation '4g' Mobile Terminals

Content Provider	IEEE Xplore Digital Library
Author	Damergi, E. Abdellatif, B.R. Bouallegue, A.
Copyright Year	2006
Description	Author affiliation: Tunis Nat. Eng. Sch. (Damergi, E.; Abdellatif, B.R.; Bouallegue, A.)
Abstract	Pipelined recurrent neural network (PRNN) has been used with lot of success in many applications. In recent works, we have also proven that the PRNN exhibits good performances when used for interference cancellation and channel parameters estimation for the different multiple access schemes proposed as physical layer of the fourth generation (4G) networks: wideband code division multiple access (WCDMA); orthogonal frequency division multiplexing (OFDM); and multi carrier CDMA (MC-CDMA). The use of a unique PRNN based module for the three multiple access techniques addresses a major challenge for the 4G mobile terminals: embedding many access techniques for reduced area and resources costs. In this paper, after a brief review of the performances of the PRNN based module used in the different multiple access receivers, we propose a mapping scheme for implementing the PRNN on a bi-directional systolic array. Finally, a neural network processing element architecture is derived
Starting Page	640
Ending Page	645
File Size	189542
Page Count	6
File Format	PDF
ISBN	8392263227
DOI	10.1109/MIXDES.2006.1706662
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	DEPT OF MICROELECTRONICS AND COMP SCIENC
Subject Keyword	Multicarrier code division multiple access Recurrent neural networks Interference cancellation Parameter estimation Costs OFDM Physical layer Multiaccess communication Wideband Pipeline processing
Content Type	Text
Resource Type	Article

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