Deterministic particle filters for joint blind equalization and decoding on frequency selective channels

This work proposes deterministic particle filtering structures for joint blindly equalizing/decoding convolutionally coded signals transmitted over frequency selective channels. After describing the proposed structures, we show how to evaluate the weight update functions corresponding to the adopted signal model. Numerical simulations show that the algorithm employing deterministic particle selection greatly outperforms alternative stochastic strategies, even when the latter employ the optimal importance function