Blind source separation of signals with known alphabets using ε-approximation algorithms

We show that blind separation of signals in given alphabets can be formulated into a quadratic optimization problem with integer constraints. Then, efficient ε-approximation algorithms are applied to directly estimate the transmitted signals. The proposed approach does not require any high order statistics. Moreover, the algorithms converge to an ε neighborhood of the global optimum with polynomial computational complexity. Simulations show that the algorithm achieves satisfactory performance using a short length of data.