Title :
Sufficient conditions for regularity and strict identifiability in MIMO systems
Author :
Moore, Terrence J. ; Sadler, Brian M.
Author_Institution :
Army Res. Lab., Adelphi, MD, USA
Abstract :
We consider regularity and identifiability of convolutive multi-input multi-output (MIMO) systems with additive white Gaussian noise, modeling the source and finite impulse response (FIR) channel sequences as deterministic unknowns. In the blind context, the MIMO system is not locally identifiable; hence, its Fisher information matrix (FIM) is not regular. In fact, the dimension of the complex-valued blind FIM space is at least the number of sources squared. Because the FIM is singular, additional information about the system is required to resolve the degrees of uncertainty and thereby obtain a valid Cramer-Rao bound (CRB); therefore, it is of interest to know under what conditions the blind FIM ity reaches its lower bound. We develop sufficient conditions for the complex FIM to attain its minimum ity, refining previous necessary conditions, and extending single-input multi-output (SIMO) results. We show that the sufficient conditions for the complex FIM to have minimum ity are also equivalent to sufficient conditions for MIMO strict identifiability. These provide sufficient conditions on the richness of the sources, the required diversity, and the source lengths. Under these conditions, additional constraints, such as training, may be employed to yield an identifiable system with no ambiguities remaining.
Keywords :
AWGN; MIMO systems; error statistics; identification; matrix algebra; signal processing; Cramer-Rao bound; MIMO systems; additive white Gaussian noise; complex-valued blind FIM space; finite impulse response channel; fisher information matrix; multiinput multioutput system; single-input multi-output; Additive white noise; Context modeling; Finite impulse response filter; MIMO; Null space; Parameter estimation; Signal processing; Statistics; Sufficient conditions; Uncertainty; Error statistics; MIMO systems; identification; parameter estimation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2004.831910