Telecommunication Systems

, Volume 68, Issue 2, pp 373–384 | Cite as

Fairness constrained diffusion adaptive power control for dense small cell network

  • Zhirong Luan
  • Hua Qu
  • Jihong Zhao
  • Badong Chen
  • Jose C. Principe


Small cell is an emerging and promising technology for improving hotspots coverage and capacity, which tends to be densely deployed in populated areas. However, in a dense small cell network, the performances of users differ vastly due to the random deployments and the interferences. To guarantee fair performance among users in different cells, we propose a new distributed strategy for fairness constrained power control, referred to as the diffusion adaptive power control (DAPC). DAPC achieves overall network fairness in a distributed manner, in which each base station optimizes a local fairness with little information exchanged with neighboring cells. We study several adaptive algorithms to implement the proposed DAPC strategy. To improve the efficiency of the standard least mean square algorithm (LMS), we derive an adaptive step-size logarithm LMS algorithm, and discuss its convergence properties. Simulation results confirm the efficiency of the proposed methods.


Fairness Dense small cell network Power control Diffusion Adaptive step-size logarithm LMS 



This work is supported by the National Natural Science Foundation of China under Grant No. 61372092 and “863” Fund under Grants 2014AA01A701

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Zhirong Luan
    • 1
  • Hua Qu
    • 1
  • Jihong Zhao
    • 1
    • 2
  • Badong Chen
    • 1
  • Jose C. Principe
    • 3
  1. 1.School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anPeople’s Republic of China
  2. 2.School of Telecommunication and Information EngineeringXi’an University of Posts and TelecommunicationsXi’anPeople’s Republic of China
  3. 3.Computational NeuroEngineering Laboratory, Department of Electrical and Computer EngineeringUniversity of FloridaGainesvilleUSA

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