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Nonconvex Optimization for Power Control in Wireless CDMA Networks

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Abstract

In this paper, we propose an efficient power control algorithm for the downlink wireless CDMA systems. The goal of our paper is to achieve the optimum and fair resource utilization by maximizing a weighted sum utility with the power constraint. In fact, the objective function in the power optimization problem is always nonconcave, which makes the problem difficult to solve. We make progress in solving this type of optimization problem using PSO (particle swarm optimization). PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. It’s proved that the proposed algorithm converges to the global optimal solutions in this paper. Numerical examples show that our algorithm can guarantee the fast convergence and fairness within a few iterations. It also demonstrates that our algorithm can efficiently solve the nonconvex optimization problems when we study the different utility functions in more realistic settings.

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Authors and Affiliations

  1. School of Mathematics and Information, Ludong University, Hongqi Middle Road 186, Zhifu District, 264025, Yantai City, Shandong Province, People’s Republic of China

    Meiqin Tang

  2. Department of Automation, School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, 200240, Shanghai, People’s Republic of China

    Chengnian Long & Xinping Guan

  3. Center for Networking Control and Bioinformatics, Department of Electrical Engineering, Yanshan University, 066004, Qinhuangdao, People’s Republic of China

    Xinping Guan

Authors
  1. Meiqin Tang
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  2. Chengnian Long
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Correspondence to Meiqin Tang.

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Tang, M., Long, C. & Guan, X. Nonconvex Optimization for Power Control in Wireless CDMA Networks. Wireless Pers Commun 58, 851–865 (2011). https://doi.org/10.1007/s11277-009-9909-7

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  • DOI: https://doi.org/10.1007/s11277-009-9909-7

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