Pseudo-Blind Algorithm for SDMA Application
Juha K. Laurila, Ernst Bonek · Kluwer Academic Publishers eBooks · 2006
We propose a novel pseudo-blind estimation method. First we estimate the basis of the desired subspace and after that we project the basis vectors obtained to the finite alphabet constellation (FA). We perform these projections using the D(W)ILSF (Decoupled (Weighted) Iterative Least Squares with Subspace Fitting) algorithm introduced in this paper. For the initialisation of the iterations we use the training sequences included in the slot structure of the GSM system. Our simulations use realistic channel model and show promising bit error rate performance also when incoming signals are not separable in angle. We also discuss complexity aspects and general advantages of the blind estimation methods. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.