Competitive Resource Allocation in HetNets: The Impact of Small-Cell Spectrum Constraints and Investment Costs

Cheng Chen*, Randall A. Berry, Michael L. Honig, Vijay G. Subramanian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Heterogeneous wireless networks with small-cell deployments in licensed and unlicensed spectrum bands are a promising approach for expanding wireless connectivity and service. As a result, wireless service providers (SPs) are adding small-cells to augment their existing macro-cell deployments. This added flexibility complicates network management, in particular, service pricing and spectrum allocations across macro- and small-cells. Further, these decisions depend on the degree of competition among SPs. Restrictions on shared spectrum access imposed by regulators, such as low power constraints that lead to small-cell deployments, along with the investment cost needed to add small cells to an existing network, also impact strategic decisions and market efficiency. If the revenue generated by small-cells does not cover the investment cost, then there will be no deployment even if it increases social welfare. We study the implications of such spectrum constraints and investment costs on resource allocation and pricing decisions by competitive SPs, along with the associated social welfare. Our results show that while the optimal resource allocation taking constraints and investment into account can be uniquely determined, adding those features with strategic SPs can have a substantial effect on the equilibrium market structure.

Original languageEnglish (US)
Article number8023872
Pages (from-to)478-490
Number of pages13
JournalIEEE Transactions on Cognitive Communications and Networking
Volume3
Issue number3
DOIs
StatePublished - Sep 2017

Funding

Keywords

  • HetNets
  • bandwidth allocation
  • investment
  • pricing
  • spectrum regulations

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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