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Optimization of Secondary User’s Performance in Cognitive Radio Network with On and Off Status

Graduate #55
Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems

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



Cognitive Radio Network (CRN) is an advanced form of wireless communication which is designed to optimize spectrum utilization. An open question of CRN is how to manage secondary user’s actions to improve the band efficiency. When a secondary user (SU) joins a CRN system, it will get a transmission reward and a possible waiting cost. Over-crowd of the SUs will lower the efficiency. Furthermore, in the real world, variety of conditions may lead band resource to unstable status which results in a random discontinuity. In this case, the roles of the system, primary users (PU) and SUs, may have varied reaction. All of them may affect the efficiency of system. In our research, we consider a CRN system with a single PU band that may be on or off randomly. We analyzed multiple possible reactions, and chose the best reasonable one combination as the main research objective. In this selected combination, we construct a Markov process model to characterize the system. By using this tool, we derive the steady-state performance of the system and then investigate the relationship between system parameters and the system efficiency. We consider both centralized and decentralized systems. In a centralized system, we deliver the optimal set of parameters. In a decentralized system, we use game theory to analyze the optimal strategy for a single SU, and then compare it to the optimal strategy for system. Finally, we propose a method to reduce the gap between them. Our numerical and simulation analysis verify the correctness of our results.

Funder Acknowledgement(s): This work is supported in part by NSF CREST program under award #1137732.

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

Role: My work throughout the whole research. Under the guidance of Dr. Li, I analyzed multiple possible reactions and selected our research combination. I constructed its mathematical model, processed numerical analysis, and programmed relative simulation as well.

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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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