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Low-Complexity Iterative Approximated Water-Filling Based Power Allocation in an Ultra-Dense Network

1
Tsinghua National Laboratory for Information Science and Technology, Research Institute of Information Technology, Tsinghua University, Beijing 100084, China
2
Broadband Wireless Access Laboratory, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3
Department of Electronic Engineering, Xiamen University, Xiamen 361005, China
*
Author to whom correspondence should be addressed.
Academic Editor: J.A. Tenreiro Machado
Entropy 2016, 18(5), 158; https://doi.org/10.3390/e18050158
Received: 28 January 2016 / Revised: 19 April 2016 / Accepted: 19 April 2016 / Published: 3 May 2016
(This article belongs to the Section Complexity)
It is highly possible that future wireless communication systems will adopt ultra-dense deployment to cope with the increasing demand on spectrum efficiency and energy efficiency. The pivotal issue to achieve the potential benefits of the ultra-dense network is to deal with the complex inter-site interference. In this paper, in order to maximize the spectrum efficiency of the system, we first make a reasonable approximation on the inter-site interference to convert the problem into a convex optimization problem. Then, the Lagrangian Multiplier method is adopted to obtain the expression of the optimum power allocation, and the water filling algorithm, as one of the most classical algorithms in the information theory, can be applied to maximize the sum rate or spectrum efficiency of the system. Since the classical iteratively searching water filling algorithm needs many iterations to converge to the optimal solution, we develop a low-complexity iterative approximate water filling algorithm. Simulation results show that the developed algorithm can achieve very close performance to the classical iteratively searching water filling based power allocation with only a few iterations under different scenarios, which leads to a significant complexity reduction. View Full-Text
Keywords: ultra-dense network; water filling algorithm; power allocation; information theory; spectrum efficiency ultra-dense network; water filling algorithm; power allocation; information theory; spectrum efficiency
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MDPI and ACS Style

Su, X.; Liu, B.; Zhu, X.; Zeng, J.; Xiao, C. Low-Complexity Iterative Approximated Water-Filling Based Power Allocation in an Ultra-Dense Network. Entropy 2016, 18, 158.

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