Optimal Overlay Cognitive Spectrum Access with F-ALOHA in Macro-Femto Heterogeneous Networks

Lu Yang, S. H. Song, Khaled B. Letaief

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The 5th generation (5G) wireless networks are conceived in the form of heterogeneous networks (HetNets), where small cells are deployed over the conventional macrocell networks to improve the spectral efficiency. In HetNets, the interference between different tiers is the main bottleneck for achieving high spectral efficiency. Many spectrum access schemes have been proposed to manage the cross-tier interference. Unfortunately, the optimal spectrum access scheme remains unknown. In this paper, we propose an F-ALOHA based cognitive spectrum access scheme for macro-femto HetNets, where the femtocells can access the idle macro-tier spectrum with a certain probability. Therefore, besides the degrees of freedom from the conventional spectrum deployment and co-tier spectrum access, the proposed scheme obtains a new degree of freedom from cross-tier spectrum access for interference management and spectral efficiency optimization. Simulation results will show that the proposed scheme outperforms existing F-ALOHA based spectrum access schemes in terms of the area spectral efficiency (ASE). More importantly, it is observed that the maximum ASE is achieved when the number of active links per unit area, which governs the interference level, reaches a certain value. The advantage of the proposed scheme comes from its ability to offload the traffic between two tiers through the cross-tier spectrum access probability, which flexibly manages the cross-tier interference.

Original languageEnglish
Article number7294683
Pages (from-to)1323-1335
Number of pages13
JournalIEEE Transactions on Wireless Communications
Volume15
Issue number2
DOIs
Publication statusPublished - 1 Feb 2016
Externally publishedYes

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Keywords

  • Area spectral efficiency
  • downlink
  • F-ALOHA
  • macro-femto HetNets
  • spectrum access

ASJC Scopus subject areas

  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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