双向拍卖结合贝叶斯模型的认知无线电网络频谱共享方案  

Cognitive radio network spectrum sharing scheme for double auction combining Bayesian model

作　　者：戴冬 王果 王磊[2] 

机构地区：[1]河南工学院计算机科学与技术系,河南新乡453003 [2]西南财经大学经济信息工程学院,四川成都610074

出　　处：《现代电子技术》2016年第11期24-29,共6页Modern Electronics Technique

基　　金：国家自然科学基金重大项目(91218301);河南省高等学校重点科研项目(16A520048)

摘　　要：针对无线电网络中频谱资源有限且利用率较低的问题,提出了基于双向拍卖结合贝叶斯推理模型的频谱共享算法。首先,主用户和次用户自适应地选择拍卖价格分享频段;然后,玩家基于反馈学习过程捕捉调整价格的策略;最后,进行重复拍卖过程直到达成共识。该算法采用了贝叶斯推理技术,能够自适应地响应不断变化的系统环境和玩家数量,具有良好的可扩展性。仿真结果表明,该算法在PU受益、交易成功率、频谱利用率、网络吞吐量等方面显著优于其他几种较新的频谱共享算法。Since the spectrum resource in radio networks is limited and its utilization is low,a spectrum sharing algorithm for double auction combining Bayesian inference model is proposed. Firstly,the primary users and the secondary users adaptively select their auction prices to share the spectrum bands. And then,based on feedback learning process,the players capture their adjustable price strategies. Finally,the auction process is repeated until the consensus is reached. The algorithm adopts Bayesian inference technique,which can adaptively response to the constantly changing system environment and players′ quantity. It has better scalability. The simulation results show that the proposed algorithm is superior to several other advanced spectrum sharing algorithms in the aspects of PU benefit,trade success rate,spectrum efficiency and network throughput.

关 键 词：贝叶斯模型 分布式方式 双向拍卖 认知无线电网络 频谱共享 

分 类 号：TN926-34[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]