Maximum likelihood detection for decode and forward cooperation with interference

In this paper, we obtain the maximum likelihood (ML) decision for a decode and forward (DF) cooperative system in Nakagami-m fading in the presence of co-channel interference at the relay as well as the destination. Through simulation results, we first show that conventional ML designed for interference free systems fails to combat the deleterious effect of interference. An optimum ML decision for combating interference is then derived for integer m. This receiver is shown to be superior to conventional ML through bit error rate (BER) performance simulations. Further, our results also indicate that optimum ML preserves relay diversity in the presence of interference.