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Stochastic Game Theory Applications for Power Management in Cognitive Networks

Fung, Sham
http://rave.ohiolink.edu/etdc/view?acc_num=kent1398286269

Abstract Details

2014, MDS, Kent State University, School of Digital Sciences.
Power allocation is a challenging issue in wireless networks and mobile communication systems, which is mainly due to the scarcity of available spectrum while trying to maximize the frequency reuse factor. Power allocation is a decision making process by a device that could severely encroach the date rate of other devices within its transmission range. Game theory is a mathematical tool that can be used to solve a multi-user decision making problem. In this thesis, we consider a cognitive network in which primary users have fixed data rate and can use various power levels, while secondary users can adjust their data rate and power level, accordingly, to maximize the spectrum utilization. The contribution of this thesis is 3-fold. First, we propose a stochastic game theory framework in which capture peculiarity that is carried by secondary users is offset by choosing appropriate power. Second, we prove the existence of achieving an equilibrium state as transmissions proceed. Third, a distributed power management algorithm, based on value iteration method, is thrived to solve the stochastic game and yields an optimal policy for each secondary user. Finally, we have developed a simulation model to test the algorithm. The simulation result shows how the total power consumption evolves with respect to the non-cooperative (misbehaving) users. The results also show how the algorithm allows users to self-adapt to changes and to equalize fast in the slow mobility environment.
Hassan Peyravi (Advisor)
Computer Science
wireless; cognitive; reinforcement learning; game theory

Recommended Citations

Citations

  • Fung, S. (2014). Stochastic Game Theory Applications for Power Management in Cognitive Networks [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1398286269

    APA Style (7th edition)

  • Fung, Sham. Stochastic Game Theory Applications for Power Management in Cognitive Networks. 2014. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1398286269.

    MLA Style (8th edition)

  • Fung, Sham. "Stochastic Game Theory Applications for Power Management in Cognitive Networks." Master's thesis, Kent State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1398286269

    Chicago Manual of Style (17th edition)

kent1398286269
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© 2014, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.
Release 3.2.12