Paper
27 July 2001 Decentralized dynamic power control for cellular spread spectrum systems
Jean-Francois Chamberland, Venugopal V. Veeravalli
Author Affiliations +
Proceedings Volume 4531, Modeling and Design of Wireless Networks; (2001) https://doi.org/10.1117/12.434450
Event: ITCom 2001: International Symposium on the Convergence of IT and Communications, 2001, Denver, CO, United States
Abstract
Power control has been recognized as an essential requirement in the design of cellular spread spectrum systems, since only by control of transmit powers can users share radio resources equitably and efficiently in a multicell environment. Much of the work on power control for spread spectrum systems found in the literature focuses on static channel models, i.e., models in which the channel gain of every user is assumed constant. In this paper, the design of dynamic power control algorithms for spread spectrum systems is considered. The design problem is posed as a tradeoff between the desire for users to maximize their individual capacity and the need to minimize the transmitted signal energy over the duration of their calls. The dynamic nature of the wireless channel for mobile users is incorporated in the problem definition. Based on a cost minimization framework, an optimal multiuser solution is derived. The multiuser solution is shown to decouple, and effectively converge to a single user solution in the large system asymptote, where the number of users and the spreading factor both go to infinity with their ratio kept constant. The proposed solution for large systems is a simple decision rule that is easily implementable in a practical system.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jean-Francois Chamberland and Venugopal V. Veeravalli "Decentralized dynamic power control for cellular spread spectrum systems", Proc. SPIE 4531, Modeling and Design of Wireless Networks, (27 July 2001); https://doi.org/10.1117/12.434450
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KEYWORDS
Control systems

Systems modeling

Computer programming

Binary data

Stochastic processes

Algorithm development

Computing systems

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