Sample Covariance Matrix Eigenvalues Based Blind SNR Estimation

被引：0

作者：

Hamid, Mohamed ^{[1
,2
]}

Bjorsell, Niclas ^{[1
]}

Ben Slimane, Slimane ^{[2
]}

机构：

[1] Univ Gavle, S-80176 Gavle, Sweden

[2] Royal Inst Technol KTH, Wirelesskth Communicat Syst Lab CoS, S-16440 Stockholm, Sweden

来源：

2014 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC) PROCEEDINGS | 2014年

关键词：

SNR estimation; Sample covariance matrix; Eigenvalues detection; Minimum Descriptive Length criterion (MDL); SPECTRUM SENSING ALGORITHMS; COGNITIVE RADIO; NOISE; SIGNAL; CHANNELS;

D O I：

暂无

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

In this paper, a newly developed SNR estimation algorithm is presented. The new algorithm is based on the eigenvalues of the sample covariance matrix of the recieved signal. The presented algorithm is blind in the sense that both the noise and the signal power are unknown and estimated from the received samples. The Minimum Descriptive Length (MDL) criterion is used to split the signal and noise corresponding eigenvalues. The experimental results are judged using the Normalized Mean Square Error (NMSE) between the estimated and the actual SNRs. The results show that, depending on the value of the received vectors size and the number of received vectors, the NMSE is changed and down to -55 dB NMSE can be achieved for the highest used values of the system dimensionality.

引用

页码：718 / 722

页数：5

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