Dimensional functional differential convergence for Cramer-Rao lower bound
Wenliang Lin, Zhongliang Deng · The Journal of Difference Equations and Applications · 2016
Channel estimations are essential to signals received. But suffering from serious channel interferences, Cramer–Rao lower Bound (CRLB) for channel estimations is avalanche and broken symmetrized, which are caused by multi-dimensional parameters heterogeneous superposition. This paper proposes dimensional functional differential convergence for CRLB. A new likelihood function estimator is designed, which fused four heterogeneous domains included time, frequency, energy and information. Variance of CRLB takes joint minimization ground state solutions for Euler–Lagrange equations. Estimations error diffusions converge by observed time and frequency perturbative results feedback. The feedback compensations modify CRLB avalanche in energy domain. New method improves channel estimations performances by decreasing CRLB diffusions. The simulations demonstrate new CRLB after convergences and modifications, enhance 7 dB Doppler frequency offset estimations, improve 16% estimations minimum mean-squared error.