A channel effect prediction-based power control scheme using PRNN/ERLS for uplinks in DS-CDMA cellular mobile systems

Authors:
Yih-Shen Chen;Chung-Ju Chang;Yi-Lin Hsieh
Affiliations:
Nat. Chiao Tung Univ., Hsinchu, Taiwan;-;-
Venue:
IEEE Transactions on Wireless Communications
Year:
2006

Citing 0
Cited 3

Nonlinear dynamic system identification using pipelined functional link artificial recurrent neural network

Neurocomputing
A novel nonlinear adaptive filter using a pipelined second-order Volterra recurrent neural network

Neural Networks
Pipelined Chebyshev functional link artificial recurrent neural network for nonlinear adaptive filter

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper proposes a channel effect prediction based power control scheme using pipeline recurrent neural network (PRNN)/extended recursive least squares (ERLS) for uplinks in direct sequence code division multiple access (DS-CDMA) cellular mobile systems. Conventional signal-to-interference (SIR) prediction-based power control schemes may incur prediction mistakes caused by the adjustment of transmission power. The proposed power control scheme purely tracks the variation of channel effect and, thus, can be immune to any power adjustment. Furthermore, it adopts the PRNN with ERLS for predicting the channel effect. Simulation results show that the channel effect prediction-based power control scheme using PRNN/ERLS achieves a 40% higher system capacity and a lower outage probability than the conventional SIR prediction-based power control scheme using grey prediction method (IEEE Trans. Veh. Technol., Vol. 49, No. 6, p. 2081, 2000).