CAJ | 학술논문

研究了认知MIMO无线网络中基于博弈论的动态频谱接入技术，以使得具有不同风险偏好的次级用户(买家)可以动态地选择竞标策略，同时主用户也可以根据系统情况，自适应地调整拍卖机制。基于非合作博弈设计了一个有限离散博弈模型，该博弈至少有一个混合策略的纳什均衡。基于自动学习机的概念，设计了一个有限反馈的分布式随机学习算法。仿真结果表明，所设计的算法具有良好的性能，与传统的固定竞拍机制和随机的选择竞价策略相比，该算法能够帮助主用户获得更高的利润，且让次级用户根据自身的风险偏好，选择一个合理的竞拍策略。
연구료인지MIMO무선망락중기우박혁론적동태빈보접입기술，이사득구유불동풍험편호적차급용호(매가)가이동태지선택경표책략，동시주용호야가이근거계통정황，자괄응지조정박매궤제。기우비합작박혁설계료일개유한리산박혁모형，해박혁지소유일개혼합책략적납십균형。기우자동학습궤적개념，설계료일개유한반궤적분포식수궤학습산법。방진결과표명，소설계적산법구유량호적성능，여전통적고정경박궤제화수궤적선택경개책략상비，해산법능구방조주용호획득경고적리윤，차양차급용호근거자신적풍험편호，선택일개합리적경박책략。
A game theoretic framework of the auction based dynamic spectrum access for multi-type buyers ( i. e. , the secondary users that have different risk preferences) in cognitive MIMO networks was presented in this paper where the auction mechanisms of the primary user are parameterized and can be adaptively designed. The proposed game is a discrete game which must have at least one mixed or pure strategy Nash equilibrium. Based on the con-cept of learning automata, a distributed algorithm was proposed to learn the Nash equilibrium of the proposed game with limited feedback. Simulation results show that our proposed algorithm is efficient and can achieve much higher performance than the traditional fixed auction mechanism schemes and the random algorithm.