DocumentCode :
2444145
Title :
Adaptive optimal predictive power control of cellular CDMA systems
Author :
Lee, Bore-kuen ; Chen, Bor-Sen ; Chen, Sheng-Kai
Author_Institution :
Dept. of Electr. Eng., Chung Hua Univ., Hsinchu, Taiwan
Volume :
1
fYear :
2004
fDate :
2-4 Sept. 2004
Firstpage :
51
Abstract :
For direct sequence code division multiple access (DS-CDMA) cellular radio systems, an autoregressive moving-average model with auxiliary input (ARMAX) process is given to model the effects of round-trip delay, channel fading, and interferences (in-cell multiple access interference and out-of-cell interference) upon the power control system. According to the predictive model corresponding to the ARMAX model, a predicitive adaptive power control scheme is proposed to compensate time delay and reduce the affects of channel fading and interference, thus achieving optimal tracking, in the sense of MMSE control error, of the desired signal-to-interference-plus-noise ratio (SINR). Due to the optimal adaptive prediction scheme, the proposed adaptive power control method does not require the statistics of fading and interferences. Several simulation results are given to confirm the performance of the proposed method.
Keywords :
adaptive control; autoregressive moving average processes; cellular radio; code division multiple access; delays; fading channels; interference suppression; least mean squares methods; optimal control; power control; predictive control; spread spectrum communication; telecommunication control; ARMAX processes; DS-CDMA systems; MMSE control error; SINR; adaptive optimal predictive power control; autoregressive moving average model; cellular radio systems; channel fading; direct sequence code division multiple access; in cell multiple access interference; optimal tracking; out of cell interference; round trip delay; signal-to-interference-plus-noise ratio; time delay compensation; Adaptive control; Delay effects; Direct-sequence code-division multiple access; Fading; Interference; Multiaccess communication; Power control; Power system modeling; Predictive models; Programmable control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN :
0-7803-8633-7
Type :
conf
DOI :
10.1109/CCA.2004.1387186
Filename :
1387186
Link To Document :
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