Low complexity minimum mean square error channel estimation for adaptive coding and modulation systems

Performance of the Adaptive Coding and Modulation (ACM) strongly depends on the retrieved Channel State Information (CSI), which can be obtained using the channel estimation techniques relying on pilot symbol transmission. Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little. In this paper, we investigate the performance of CSI prediction using the Minimum Mean Square Error (MMSE) channel estimator for an ACM system. To solve the two problems of MMSE: high computational operations and oversimplified assumption, we then propose the Low-Complexity schemes (LC-MMSE and Recursion LC-MMSE (R-LC-MMSE)). Computational complexity and Mean Square Error (MSE) are presented to evaluate the efficiency of the proposed algorithm. Both analysis and numerical results show that LC-MMSE performs close to the well-known MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.