Realistic framework for resource allocation in macro–femtocell networks based on genetic algorithm

Hanaa Marshoud, Hadi Otrok, Hassan Barada, Rebeca Estrada, Abdallah Jarray, Zbigniew Dziong

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In this paper, we consider the problem of resource allocation in non-dense macrocell–femtocell networks. We build a comprehensive realistic framework that overcomes the limitations of previous research work such as (1) resources underutilization due to the equal transmitted power per subcarrier in macrocell, (2) lack of femtocells selection mechanism that grant access to public users without depriving their own subscribers. Orthogonal Frequency Division Multiple Access is a promising candidate for efficient spectrum sharing techniques as it eliminates intracell interference. We propose a base station selection and resource allocation model for two-tier networks that is able to: (i) maximize the overall network throughput, (ii) find the appropriate serving base station for each mobile user, and (iii) jointly assign bandwidth and power to each user. The proposed approach is based on Genetic Algorithm (GA) technique since this technique allows to find a near optimal solution and to speed up the optimization process. Simulations are conducted under realistic scenarios where user mobility and resource reservation are taken into account. The performance of the proposed approach is compared with a Mixed Integer Linear Programming (MILP) approach and the Weigthed Water Filling (WWF) algorithm.

Original languageBritish English
Pages (from-to)99-110
Number of pages12
JournalTelecommunication Systems
Volume63
Issue number1
DOIs
StatePublished - 1 Sep 2016

Keywords

  • Femtocell
  • Genetic algorithm
  • Linear programming
  • Macrocell
  • Optimization theories
  • Resource allocation

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