Self organizing map based channel prediction for OFDMA

Author

Senevirathna, H.M.S.B. ; Yamashitha, Katsumi ; Lin, Hai

Author_Institution

Dept. of Electr. & Electron. Syst., Osaka Prefectural Univ., Sakai, Japan

fYear

2005

fDate

23-26 May 2005

Firstpage

2506

Abstract

Channel prediction is the key requirement in adaptive transmission techniques such as adaptive modulation, adaptive coding and adaptive power control. The paper presents a novel self organizing map (SOM) based channel predictor for the downlink of an orthogonal frequency-division multiple access (OFDMA) system. The proposed predictor uses a Kalman trained-SOM backed mixtures of experts (ME) modular neural network. The performance of the predictor is evaluated on an OFDMA system with a system delay where channel prediction is needed.

Keywords

OFDM modulation; adaptive systems; delays; frequency division multiple access; learning (artificial intelligence); prediction theory; self-organising feature maps; telecommunication computing; Kalman trained self organizing map; OFDM; OFDMA; adaptive coding; adaptive modulation; adaptive power control; adaptive transmission techniques; channel prediction; delay; mixtures of experts modular neural network; orthogonal FDMA; orthogonal frequency-division multiple access; Adaptive coding; Adaptive control; Delay systems; Downlink; Kalman filters; Modulation coding; Neural networks; Organizing; Power control; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on

Print_ISBN

0-7803-8834-8

Type

conf

DOI

10.1109/ISCAS.2005.1465135

Filename

1465135