Multistage Bayesian Game based Spectrum Trading for Cognitive Radio Networks

• Main Authors: Lee, Chong-You, 李重佑
• Other Authors: Chien, Feng-Tsun
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/20682410269255307778

碩士 === 國立交通大學 === 電子工程系所 === 98 === In this thesis, we study the problem of spectrum trading in cognitive radio (CR) networks from a game theoretical perspective. Particularly, we consider a CR network with multiple primary services (PSs) and multiple secondary services (SSs), where all PSs are sellers targeting at setting the prices for spectrum leasing and SSs are buyers deciding how much spectrum are demanded from each PS in the trading game. Aiming at dealing with the trading behaviors, we propose using a multistage Bayesian game based trading model to account for possible unknown private information in each player, and obtain the perfect Bayesian equilibrium (PBE) sequentially under a bandwidth constraint, which requires all SSs' demanded bandwidth not exceeding that the PS can possibly offer and each SS's demand should not be negative. Following the backward induction principle, we transfer the Karush-Kuhn-Tucker (KKT) condition of the SSs into each PS's optimization constraint, and collectively form joint KKT conditions that satisfy the bandwidth constraint. We present an active-set based algorithm to solve the joint KKT conditions, and analyze the corresponding complexity. Furthermore, the convergence behaviors of the action profiles and the beliefs of the unknown information are also investigated in the work. Finally, in the simulations, we compare the proposed approach with earlier work and numerically study the convergence behaviors of the proposed multistage game.