Journal on Communications ›› 2013, Vol. 34 ›› Issue (4): 201-206.doi: 10.3969/j.issn.1000-436x.2013.04.025

• Academic communication • Previous Articles    

New SNR estimation algorithm based on relevance vector machine

Bo HAN,Jie WU,Hua XU,Hai-ou SHEN,Peng LI   

  1. School of Information and Navigation,Air Force Engineering University,Xi’an 710077,China
  • Online:2013-04-25 Published:2017-07-17
  • Supported by:
    The National Natural Science Foundation of China

Abstract:

A new SNR estimation algorithm based on relevance vector machine (RVM) was proposed,it can not only be used under the flat 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 moments and four-order moments,and the reliable weights of the model can be figured out by straining and studying.Simulation 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.

Key words: SNR estimation, flat fading channel, relevance vector machine, weight

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