摘要
为了提高数据链系统的时隙利用率,提出一种基于固定和动态时隙预约相融合的TDMA分配算法。采用固定时隙分配算法对部分时隙进行分配,用极限学习机对用户业务量进行预测,并根据预测结果确定所需时隙数,这样可以根据不同业务特点动态调整时隙分配策略,以满足用户通信需求;最后使用OPNET仿真软件对算法性能进行测试。实验结果表明,相对其他时隙分配算法,该算法提高了时隙利用率,大幅度减少了平均时延。
To improve the performance of tactical data link system,a new slot allocation algorithm is proposed based on static and dynamic slot allocation algorithm.Firstly,the static slot assignment algorithm is used to assign part time slot,and then the extreme learning machine is used to predict the user traffic volume,and the required number of slots is determined according to the prediction results,so the communication requirements of user is met according to different business characteristics by dynamic adjustment slot allocation strategy,finally the simulation experiments are used to test the performance of the algorithm in OPNET platform.The results show that the proposed algorithm has improved the slot utilization rate and reduces the average delay.
出处
《计算机工程与应用》
CSCD
北大核心
2015年第13期92-95,144,共5页
Computer Engineering and Applications
关键词
战术数据链
业务预测
极限学习机
固定时隙分配算法
tactical data link
traffic prediction
extreme learning machine
static slot assignment algorithm
