Joint Channel Estimation and Data Detection for SIMO Systems: An EM-Based Approach

The single-input multi-output (SIMO) channel model is widely used in data transmission and diversity receptions. In this paper, we present three computationally efficient iterative receivers for joint channel estimation and data detection in SIMO systems. These receivers result from an application of the expectation-maximization (EM) and the space-alternating generalized expectation-maximization (SAGE) algorithms. Bit error rate (BER) performance of the Maximum Likelihood (ML) receivers with perfect channel state information (CSI) is plotted and compared with the BER performance of the proposed iterative receivers. Proposed receivers exhibit near ML performance with a few iterations.