摘要
认知无线网络(cognitive radio network,CRN)中,为降低认知用户对授权用户干扰,需尽可能的减少频谱切换次数。提出了一种基于预测信道空时间(prediction of the channel idle time,PCIT)的认知无线动态频谱切换方法。该方法基于已知状态序列的隐马尔可夫模型(known-state sequence hidden Markov model,KSS-HMM),利用信道状态的历史信息预测信道未来空闲时间期望及传输数据包的数量,并给出了备选信道的选择方法,通过比较每个备选信道的传输数据量来选择最佳信道进行数据传输。仿真结果表明,与随机信道选择和传统选择方法相比,该方法能明显减少信道切换次数,同时提高了认知用户的吞吐量。
For the interference reduction from cognitive users to licensed users, it is important to minimize the num- ber of spectrum handoff as much as possible in cognitive radio network （CRN）. In this paper,a dynamic spectrum handoff method using prediction of the channel idle time （PCIT） is proposed. Based on know-state sequence hid- den Markov model （KSS-HMM） ,it forecasts the expectation of idle channels and the number of transmitting data packets in the future based on historical information of channel states, also gives the ways to select backup chan- nels. The amount of transmitting data packet of each backup channel is calculated and the best channel to transmit data via comparing the amount of transmitting data packets of each backup channel is chosen. The simulation re- sults show that the proposed method outperforms the random channel selection and intelligent channel selection with more channel switching times reduction and throughput increase.
出处
《电子测量与仪器学报》
CSCD
2014年第1期69-74,共6页
Journal of Electronic Measurement and Instrumentation
基金
安徽省自然科学基金(2012AKZR0330)
中国博士后基金(2012M521247)
中央高校基本科研业务费专项资金(2011HGBZ129
2012HGQC0014)项目资助
