航空通信网络信道接入的统计预测机制  

Statistical prediction mechanism for channel access in aeronautical communication network

作　　者：卓琨[1] 张衡阳[1] 戚云军[1] 郑博[1,2] 张毅卜 

机构地区：[1]空军工程大学信息与导航学院 [2]解放军94188部队 [3]空军大连通信士官学校

出　　处：《计算机工程与设计》2015年第8期2001-2006,共6页Computer Engineering and Design

基　　金：国家自然科学基金项目(61202490);航空科学基金项目(2013ZC15008)

摘　　要：针对航空通信网络中随机竞争机制在负载较重时会产生网络性能恶化的问题,提出一种适用于航空通信网络信道接入的统计预测机制。在对信道忙闲程度等级进行划分的基础上,利用滑动窗口机制和Bayes理论对下一时刻信道忙闲程度的精确预测区间进行估计,结合信道忙闲程度的出现频次和马氏链的状态转移矩阵实现对下一时刻信道忙闲程度的精确预测,为网络节点如何动态调整分组发送概率提供依据。理论分析和仿真结果表明,该机制具有更精确的预测性能,降低了分组接入的冲突概率,提高了信道利用率。Aiming at solving the problem that the random competition mechanism brings about network performance deteriora- tion when network load becomes heavy, a statistical prediction mechanism applied to channel access in aeronautical communica- tion network was proposed. The channel busy-idle （BI） degree＇s possible prediction interval belonging to next time interval was estimated using sliding window mechanism and Bayes theory based on multi-division of channel BI degree, and the precise predic- tion of prospective channel BI degree was obtained according to channel BI degree appearance frequency in history information and the state-transition matrix of Markov chain, therefore network node adjusted their block probabilities of transmissions according to the prediction result. The results of theoretical analysis and simulation indicate that the prediction accuracy is improved obviously using the mechanism, the collision probability of block access is decreased, and the channel utilization is enhanced.

关 键 词：航空通信网络 信道接入 忙闲程度 BAYES预测 马尔科夫链 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]