NDLI: Using adaline neural network for performance improvement of smart antennas in TDD wireless communications

Content Provider	IEEE Xplore Digital Library
Author	Kavak, A. Yigit, H. Ertunc, H.M.
Copyright Year	1990
Abstract	In time-division-duplex (TDD) mode wireless communications, downlink beamforming performance of a smart antenna system at the base station can be degraded due to variation of spatial signature vectors corresponding to mobile users especially in fast fading scenarios. To mitigate this, downlink beams must be controlled by properly adjusting their weight vectors in response to changing propagation dynamics. This can be achieved by modeling the spatial signature vectors in the uplink period and then predicting them to be used as beamforming weight vectors for the new mobile position in the downlink transmission period. We show that ADAptive LInear NEuron (ADALINE) network modeling based prediction of spatial signatures provides certain level of performance improvement compared to conventional beamforming method that employs spatial signature obtained in previous uplink interval. We compare the performance of ADALINE with autoregressive (AR) modeling based predictions under varying channel propagation (mobile speed, multipath angle spread, and number of multipaths), and filter order/delay conditions. ADALINE modeling outperforms AR modeling in terms of downlink SNR improvement and relative error improvement especially under high mobile speeds, i.e., V=100 km/h.
Sponsorship	IEEE Computational Intelligence Society
Page Count	10
File Size	494449
Starting Page	1616
Ending Page	1625
File Format	PDF
ISSN	10459227
Volume Number	16
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Wireless communication Downlink Array signal processing Vectors Predictive models Mobile antennas Antennas and propagation Base stations Degradation vector channel Adaline network autoregressive model beamforming linear prediction smart antennas
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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