Adaptive decision aided turbo equalization of unknown channels using SOVA and MAP decoding algorithms

The computational complexity of a turbo equalizer with decision aided equalizer is analysed. We considered two different decoding algorithms named MAP and SOVA together with the adaptive equalization scheme. The channel is assumed to be unknown. The training sequence is provided in order to estimate the channel impulse response. The implementations of decoding algorithms require different computational complexities. Simulation results show that the same BER performance is obtained for different channels using both decoding algorithms although SOVA performs significantly less number of computations.