Abstract
We study two (classes of) distributed algorithms for power control in a general model of wireless networks. There are n wireless communication requests or links that experience interference and noise. To be successful a link must satisfy an SINR constraint. The goal is to find a set of powers such that all links are successful simultaneously. A classic algorithm for this problem is the fixed-point iteration due to Foschini and Miljanic [8], for which we prove the first bounds on worst-case running times – after roughly O(n logn) rounds all SINR constraints are nearly satisfied. When we try to satisfy each constraint exactly, however, convergence time is infinite. For this case, we design a novel framework for power control using regret learning algorithms and iterative discretization. While the exact convergence times must rely on a variety of parameters, we show that roughly a polynomial number of rounds suffices to make every link successful during at least a constant fraction of all previous rounds.
This work has been supported by DFG through UMIC Research Centre, RWTH Aachen University, and grant Ho 3831/3-1.
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Dams, J., Hoefer, M., Kesselheim, T. (2011). Convergence Time of Power-Control Dynamics. In: Aceto, L., Henzinger, M., Sgall, J. (eds) Automata, Languages and Programming. ICALP 2011. Lecture Notes in Computer Science, vol 6756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22012-8_51
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DOI: https://doi.org/10.1007/978-3-642-22012-8_51
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