We describe a method for Maximum Likelihood (ML) parameter estimation corrupted by additive white Gaussian noise. The ML cost function is maximized over the constraint
that the detected data vector lie on the sphere. The results are compared with MMSE and with [2]. Simulations results shows superior performance of our method comparing to both the methods.
Type:
Conférence
City:
Moscow
Date:
2003-03-14
Department:
Systèmes de Communication
Eurecom Ref:
1122
See also:
