On the Robustness of Digital Modulation Recognition for Cooperative Relaying Networks under Imperfect CSI

Cognitive radio (CR) technology offers the ability to adapt the transmission or reception parameters, thus efficiently improving the wireless spectrum resources utilization. As one of the important components of CR, automatic modulation recognition (AMR) aims to improve the overall communication performance besides promoting efficient and secure transmissions. In this paper, we tackle the semi blind modulation recognition problem in a distributed space-time block coding (D-STBC) scheme for a cooperative relaying network of three nodes, employing the Amplify-and-Forward (AaF) protocol. As classifier, we design a multi-layer artificial neural network (ANN) and train it using higher-order statistics (HOS) as features of the received signals. We evaluate two D- STBC configurations identifying the modulation with and without channel state information (CSI) by exploiting both the temporal and spatial signal dimensions. Experimental results demonstrate that the proposed identifier ensures a good probability for achieving correct modulation identification in acceptable signal-to-noise ratio (SNR) ranges.