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Pareto Optimal Power Control via Bisection Searching in Wireless Networks

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4 Author(s)
Li Ping Qian ; Coll. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China ; Yuan Wu ; Shengli Zhang ; Qingzhang Chen

In this letter, we first prove that the upper boundary of the feasible signal to interference-plus-noise ratio (SINR) region achieved by power control is Pareto optimal under the constraints of minimum SINR requirements and limited power. Thanks to the Pareto optimal nature, we further propose a bisection searching based low-complexity algorithm that achieves arbitrary Pareto optimal power control over the entire feasible SINR region. More importantly, we can easily approach the upper boundary of the feasible SINR region through the proposed algorithm.

Published in:

Communications Letters, IEEE  (Volume:17 ,  Issue: 4 )

Date of Publication:

April 2013

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