TY - JOUR
T1 - MMSE-based MDL method for accurate source number estimation
AU - Huang, Lei
AU - Long, Teng
AU - Mao, Erke
AU - So, H. C.
PY - 2009
Y1 - 2009
N2 - In civilian communication systems, the signature sequence of the desired signal in training phase is known to the receiver. In this letter, using the mutual information, we bridge the probability density function and minimum mean-square error (MMSE) between the observed data and training sequence of the desired signal, and then employ the MMSE to construct a minimum description length (MDL) criterion for accurate source enumeration. Numerical results demonstrate that the proposed method is superior to existing MDL methods in terms of detection performance particularly for small number of snapshots and/or source angular separation.
AB - In civilian communication systems, the signature sequence of the desired signal in training phase is known to the receiver. In this letter, using the mutual information, we bridge the probability density function and minimum mean-square error (MMSE) between the observed data and training sequence of the desired signal, and then employ the MMSE to construct a minimum description length (MDL) criterion for accurate source enumeration. Numerical results demonstrate that the proposed method is superior to existing MDL methods in terms of detection performance particularly for small number of snapshots and/or source angular separation.
KW - Eigenvalue decomposition
KW - Minimum description length
KW - Sensor array processing
KW - Source number estimation
UR - http://www.scopus.com/inward/record.url?scp=79951730524&partnerID=8YFLogxK
U2 - 10.1109/LSP.2009.2024785
DO - 10.1109/LSP.2009.2024785
M3 - Article
AN - SCOPUS:79951730524
SN - 1070-9908
VL - 16
SP - 798
EP - 801
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
IS - 9
M1 - 2024785
ER -