Samples Covariance Matrix Eigenvalues Based Blind SNR Estimation
2014 (English)In: Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International, 2014, 718-722 p.Conference paper (Refereed)
In this paper, a newly developed SNR estimation algorithm is presented. The new algorithm is based on the eigenvalues of the samples 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 received vectors size, N, and the number of received vectors, L, the NMSE is changed and down to -55 dB NMSE can be achieved for the highest used values of N and L.
Place, publisher, year, edition, pages
2014. 718-722 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-140706DOI: 10.1109/I2MTC.2014.6860836ScopusID: 2-s2.0-84905695374OAI: oai:DiVA.org:kth-140706DiVA: diva2:692349
IEEE Int. Conf. on Instrumentation and Measurement Technology (I2MTC), 2012
QC 201502092014-01-302014-01-302015-02-10Bibliographically approved