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Improved Genetic Algorithm for Downlink Carrier Allocation in an OFDMA System

  • Nader El-Zarif
  • Mariette Awad
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 586)

Abstract

Different intelligent techniques have been proposed to solve the problem of downlink resource allocation in orthogonal frequency division multiple access (OFDMA)-based networks. These include mathematical optimization, game theory and heuristic algorithms. In an attempt to improve the performance of traditional genetic algorithm (GA) and its heuristics, we propose an improved GA (IGA) that optimizes the search space and GA iterations. Using concepts from ordinal optimization (OO) to determine the stopping criteria and sub-sampling alternatives to generate the initial population, IGA shows faster convergence when applied to downlink carrier allocation in an OFDMA system. IGA workflow also includes a new “swap if better”‘ mutation operator that replaces the random mutation and a novel fitness function that seeks to maximize the total throughput while minimizing the under-allocation in an attempt to meet the quality of service (QoS) requirements for different types of users. Comparing performance of IGA with different fitness functions published in literature shows improved fairness, comparable throughput and standard deviation. Most importantly IGA is able to better meet the QoS requirements for the different types of users (real time and non real-time) and this, within few milliseconds, making it attractive for real time implementation. Future work plans a parallel implementation of IGA to further improve its computational time.

Keywords

Genetic Algorithm Orthogonal Frequency Division Multiple Access Good Effort Nash Bargaining Solution Subscriber Station 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.American University of BeirutBeirutLebanon

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