tailieunhanh - Báo cáo hóa học: " Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 89864 Pages 1-13 DOI ASP 2006 89864 Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks Mohammed M. Olama 1 Seddik M. Djouadi 1 and Charalambos D. Charalambous2 1 Department of Electrical and Computer Engineering University of Tennessee Knoxville TN 37996 USA 2 Department of Electrical and Computer Engineering University of Cyprus 1678 Nicosia Cyprus Received 1 June 2005 Revised 4 March 2006 Accepted 7 April 2006 A new time-varying TV long-term fading LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models the statistics of the proposed model are shown to be TV but converge in steady state to their static counterparts. Moreover optimal power control algorithms PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies PPCS are used. In addition an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models and the distributed stochastic PCA provides better power stability and consumption than the

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