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Non-cooperative and Cooperative Joining Strategies in Multi-band Cognitive Radio Networks with Perfect or Imperfect Sensing

Graduate #49
Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems

Nan Li - Texas Southern University
Co-Author(s): Wei Wayne Li, Texas Southern University, Houston, TX



In the most of the current cognitive radio (CR) analytical models, the single primary user (PU) band is used to explore the strategic behavior of the secondary users (SUs). This study focuses on investigating the joining behavior of SUs in a CR network which is composed of multiple PU bands and no waiting queue. If there are some available bands in the system, on one hand, the arriving SU can join in the system immediately; on the other hand, the SUs within the system won’t be interrupted by the joining PU. However, if all the bands are occupied, the arriving SU must give up its further service due to the absence of the queue. Besides, one SU’s service on the band will be terminated whenever a PU arrives. The information of the numbers of SUs and PUs, and the SUs’ sensing ability are the key points that need to be considered in the different cases. Three different cases of the system are investigated under non-cooperative joining strategy (maximize the benefit in a selfish way) and cooperative joining strategy (maximize the sum of the welfares by cooperating with each other). In the first case, there is no quantity information of SU and PU, and the SUs have the perfect sensing ability. The second case also has no quantity information, but the sensing ability of SUs is imperfect. In the last case, the number of SU and PU are known. SU and PU have the perfect sensing ability to acquire the threshold of accepting SU. Some numerical analysis and visualizations are implemented to test the performances of the CR network under different circumstances.

Not Submitted

Funder Acknowledgement(s): This work was supported partially by the National Science Foundation under grant NSF-1137732.

Faculty Advisor: Wei Wayne Li, liww@tsu.edu

Role: Description of the model, analysis the result, visualization and conclusion

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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