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A multi-greedy spectrum auction algorithm for cognitive small cell networks

Author

Listed:
  • Feng Zhao
  • Bo Liu
  • Hongbin Chen

Abstract

Cognitive small cell networks consisting of macro- and small cells are foreseen as a candidate solution to meet ever increasing requirements of broadband services and new applications. However, the traditional fixed spectrum allocation policy makes available spectrum resources for small cells insufficient. Therefore, an efficient spectrum allocation method is urgently needed that allows a large number of small cells to share spectrum resources with macro-cells. In this article, a real-time spectrum auction model is presented which aims at assigning the scarce spectrum resources to small cells quickly. The co-win situation is constructed, and the trade-off between spectrum utilization and revenues is controlled. Such a problem is formulated as an NP-hard optimization problem for which a low-complexity multi-greedy algorithm is proposed to obtain prices and spectrum allocations. The proposed algorithm can achieve conflict-free spectrum allocations that maximize the utility and spectrum allocation efficiency. Compared with the Vickrey–Clarke–Groves algorithm, simulation results show the higher utility and spectrum allocation efficiency of the proposed algorithm.

Suggested Citation

  • Feng Zhao & Bo Liu & Hongbin Chen, 2017. "A multi-greedy spectrum auction algorithm for cognitive small cell networks," International Journal of Distributed Sensor Networks, , vol. 13(6), pages 15501477177, June.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:6:p:1550147717717215
    DOI: 10.1177/1550147717717215
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