基于相关向量机的信噪比估计算法  

New SNR estimation algorithm based on relevance vector machine

作　　者：韩博[1] 吴杰[1] 许华[1] 沈海鸥[1] 李鹏[1] 

机构地区：[1]空军工程大学信息与导航学院,陕西西安710077

出　　处：《通信学报》2013年第4期201-206,共6页Journal on Communications

基　　金：国家自然科学基金资助项目(61001111)~~

摘　　要：为了使已有PSK信号信噪比估计算法在平坦衰落信道下,能够同时满足估计范围大、估计精度高的要求,提出了一种基于相关向量机(RVM,relevance vector machine)的信噪比估计新算法。该方法在建立起信噪比与二阶、四阶矩之间关系的基础上,应用相关向量机建立估计模型,并通过训练学习,得到可靠的模型权值。实验表明,利用测试数据对信号信噪比进行估计时,相对于其他算法,该算法具有使用数据量少,估计范围广,在有效的估计范围内,估计精度较高,且适用于多种调制信号的特点。A new SNR estimation algorithm based on relevance vector machine （RVM） was proposed, it can not only be used under the fiat fading channel, but also meet the request of larger estimation range and higher estimation accuracy of PSK. The estimation model was created by using RVM, based on the relation between the SNR and the two-order mo- ments and four-order moments, and the reliable weights of the model can be figured out by straining and studying. Simu- lation results show that this algorithm has lots of advantages, for example, it uses less data and has larger estimation range than general algorithm, in addition, its estimation accuracy becomes higher in the effective estimation rang, and it is applicable to more modulation signals.

关 键 词：信噪比估计 平坦衰落信道 相关向量机 权值 

分 类 号：TN911.7[电子电信—通信与信息系统]