Distributed and Centralized Schemes for Channel Sensing Order Setting in Multi-user Cognitive Radio Networks

  • Authors:

  • Junyuan Huang;Huaibei Zhou;Yongqun Chen;Bo Chen;Ruoshan Kong

  • Affiliations:

  • School of Physics and Technology, Wuhan University, Wuhan, China 430072;International school of software, Wuhan University, Wuhan, China 430072;School of Physics and Technology, Wuhan University, Wuhan, China 430072;School of Physics and Technology, Wuhan University, Wuhan, China 430072;International school of software, Wuhan University, Wuhan, China 430072

  • Venue:
  • Wireless Personal Communications: An International Journal
  • Year:
  • 2014

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Abstract

Channel sensing order setting is crucial for efficient channel exploration and exploitation in cognitive radio (CR) networks. This paper investigates the sensing order setting problem in multi-channel multi-user CR networks for both distributed scenario and centralized scenario. As the optimal solution is too complicated, two suboptimal greedy search algorithms with much less computational complexities are proposed. The channel availability, channel achievable rate, multi-user diversity and collisions among CR users are considered comprehensively in our proposed methods. For the distributed scenario, a novel potential function is proposed to represent the relative advantage of a channel used by a user among multi channels and multi users, based on which each user can get its own sensing order. For the centralized scenario, a sensing matrix is obtained by a coordinator for all the users. It is shown that, CR users' average throughput increases and collision probability decreases with the number of channels due to increased transmission opportunities. The total network throughput increases with the number of user pairs due to multi-user diversity. Simulation results validate the efficacy of the proposed schemes in elevating CR users' throughput and decreasing the probability of collision, and show the performance improvement of the proposed schemes by comparisons with existing works.