• DocumentCode
    5236
  • Title

    Distributed Subchannel Allocation for Interference Mitigation in OFDMA Femtocells: A Utility-Based Learning Approach

  • Author

    Chao Xu ; Min Sheng ; Xijun Wang ; Cheng-Xiang Wang ; Jiandong Li

  • Author_Institution
    State Key Lab. of Integrated Service Networks, Xidian Univ., Xi´an, China
  • Volume
    64
  • Issue
    6
  • fYear
    2015
  • fDate
    Jun-15
  • Firstpage
    2463
  • Lastpage
    2475
  • Abstract
    Both orthogonal frequency-division multiple access (OFDMA) and femtocell are promising technologies providing subscribers with better services. However, due to the ad hoc nature of femtocells, there is a great challenge to mitigate interference, which may seriously compromise the benefits promised by this novel network architecture. This paper investigates the distributed subchannel allocation (DSA) for cotier interference mitigation in OFDMA-based femtocells, where the femtocells and macrocell transmit on orthogonal subchannels. Particularly, to intuitively study system performance, we formulate this problem as a noncooperative rate maximization game where the utility of each player or femtocell access point is its capacity instead of the incoming interference. Unfortunately, the uncertainty of the existence of the Nash equilibrium for this game makes it difficult to design efficient distributed schemes. To address this issue, we introduce a state space to reflect players´ desire for new strategies and then devise a utility-based learning model that requires no information exchange between different players. Utilizing this model, a utility-based DSA algorithm is developed. Moreover, it is analytically shown that the Pareto-optimal solution can be achieved with our proposed algorithm, and as a result, the overall capacity can be efficiently improved, and the system interference can be efficiently mitigated. Finally, simulation results verify the validity of our analysis and demonstrate that our scheme performs comparably or even better compared with the existing strategies, which require information exchange among different femtocells.
  • Keywords
    OFDM modulation; femtocellular radio; frequency division multiple access; game theory; interference suppression; learning (artificial intelligence); mobile computing; DSA algorithm; Nash equilibrium; OFDMA femtocells; Pareto-optimal solution; cotier interference mitigation; distributed subchannel allocation; network architecture; noncooperative rate maximization game; orthogonal frequency-division multiple access; orthogonal subchannels; state space; utility-based learning approach; Algorithm design and analysis; Femtocell networks; Femtocells; Games; Interference; Resource management; Tin; Distributed subchannel allocation; Pareto optimality; femtocells; interference mitigation; orthogonal frequency-division multiple access (OFDMA);
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2014.2344434
  • Filename
    6868315