Cooperation among wireless service providers: opportunity, challenge, and solution

  • Authors:
  • Peng Lin;Juncheng Jia;Qian Zhang;Mounir Hamdi

  • Affiliations:
  • Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology

  • Venue:
  • IEEE Wireless Communications
  • Year:
  • 2010

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Abstract

Current wireless service market is shared by several major wireless service providers, who rely on mutually exclusive spectrum bands for service provision. The usage of these spectrum bands is limited to specific WSPs and wireless access technologies regulated by government, which is the typical method of interference management. However, our recent large-scale spectrum occupancy measurement study reveals significantly unbalanced usage of spectrum bands owned by different WSPs in several representative locations in China. Such imbalance is mainly due to the mismatch of static spectrum allocation and dynamic spectrum demand. This motivates us to consider cooperation among WSPs to share their resources in terms of infrastructure and spectrum. Compared with infrastructure-based cooperation, spectrum-based cooperation avoids the overhead of tight interoperation among the WSPs involved, which is a novel resource sharing model and also supported by the recent move of dynamic spectrum management. With such spectrum-based cooperation in mind, we propose a new wireless market paradigm, where future wireless service provisioning will probably be associated with cooperation in the form of spectrum resource exchange: while each WSP has its own deployed infrastructure (including multiple base stations) and operating spectrum, they can cooperate with each other to share their spectrum in the form of time portions. To study the above resource exchange, we adopt the group bargaining solution concept, which can well model the interaction among WSPs (as groups of base stations). To address the scalability and privacy issues in practice, we propose to use two types of distributed algorithms: local bargaining and Lagrangian decomposition. Simulation has been conducted for verification and performance comparison.