A code-aided iterative receiver applied to AF two-way relay MC-CDMA systems

In this paper, a code-aided maximum likelihood (ML) iterative algorithm is proposed for amplify-and-forward (AF) two-way relay multicarrier code division multiple access (MC-CDMA) systems. The system which consists of two source terminals and a relay node works with a two-phase protocol. In order to estimate the cascaded channel and reliably detect the data from the other terminal, the estimator utilizes the log-likelihood ratio (LLR) value from the decoder as posteriori probabilities for the next estimation, and the decoder will re-decode the information based on the new channel state information (CSI), thus the cycle continues until a stable state is obtained. Simulation results demonstrate that an impressive improvement can be obtained compared with the training-based method, and the proposed algorithm converges with a fast speed¹.