Blind SNR estimation for OFDM signals in cognitive radio

Ming-qian LIU; Bing-bing LI; Ning-jie TANG; Zhao LI

doi:1000-436X(2011)11-0078-07

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Blind SNR estimation for OFDM signals in cognitive radio

Papers | 更新时间：2024-06-05

- Blind SNR estimation for OFDM signals in cognitive radio
- Journal on Communications Vol. 32, Issue 11, Pages: 78-84(2011)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：1000-436X(2011)11-0078-07
  CLC： TN911.7
- Online First：2011-11，
  
  Published：25 November 2011
- 稿件说明：
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Ming-qian LIU, Bing-bing LI, Ning-jie TANG, et al. Blind SNR estimation for OFDM signals in cognitive radio[J]. Journal on Communications, 2011, 32(11): 78-84.
DOI：

Ming-qian LIU, Bing-bing LI, Ning-jie TANG, et al. Blind SNR estimation for OFDM signals in cognitive radio[J]. Journal on Communications, 2011, 32(11): 78-84. DOI： 1000-436X(2011)11-0078-07.

摘要

针对认知正交频分复用(OFDM

orthogonal frequency division multiplexing)系统中低信噪比多径信道下传统的OFDM信号信噪比盲估计算法的估计性能差，计算复杂度高的问题，提出一种新的OFDM信号信噪比盲估计方法，该方法首先利用自相关函数的特性粗略估计出信道阶数，确定循环前缀部分中不受符号间干扰的数据区间，然后根据选定区间的数据的自相关函数值估计接收信号的信号功率，最后利用循环前缀数据为部分有用数据的复制这一特性估计出噪声功率，从而估计出接收信号的信噪比。仿真实验结果表明，提出的方法无需任何先验信息，在低信噪比多径信道下具有良好的估计性能，且计算复杂度低，更适合于认知OFDM系统。

Abstract

The traditional blind SNR estimation algorithms had problems of poor performance and high computation complexity for OFDM systems in cognitive radio with low signal to noise ratio(SNR)and multi-path channel conditions

in view of which a novel blind SNR estimation method for orthogonal frequency division multiplexing(OFDM)signals was proposed.Firstly

the channel order was roughly estimated by utilizing the characteristics of autocorrelation function to determine the data interval which was free of inter-symbol interference(ISI).Secondly

the signal average power was estimated by computing the autocorrelation values of data in the determined interval.Finally

the noise average power was estimated by utilizing the characteristics that the data in cyclic prefix which was replication of part useful data.So the SNR of the received signals could be estimated.The simulation results show that the proposed method doesn’t need any prior information and has better performance and lower computation complexity

which is more suitable for OFDM systems in cognitive radio.

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Keywords

references

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