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Efficient Method for SBI Estimation in Iterative Coded MIMO Systems


Zuhaibuddin Bhutto, Saleem Ahmed, Muhammad Zahid Tunio, D.M.S Bhatti, Jalal Shah, Kashif Saleem, and Sohrab Khan


Vol. 19  No. 6  pp. 135-140


In this research article, we exhibit a low complexity method for a multiple-input-multiple-output (MIMO) system with forward error correction (FEC) through soft interference cancellation minimum mean-squared error (SIC-MMSE) linear detecting method, which has improved performance compared with the existing methods. In traditional SIC-MMSE detector, the complexity of performing the inverse operation grows as we increase antenna size and number of iterations if we employ iterative MIMO system, where information is shared amongst FEC channel decoder and soft MIMO detector which is commonly called joint iterative detection and decoding (JIDD) system. One other issue in SIC-MMSE is the extraction of soft information whose complexity depends on extraction approach. The traditional SIC-MMSE method uses the maximum a posteriori (MAP) method to find the soft information. We propose a hybrid method to reduce its complexity. This hybrid method is based on an evaluation of soft information by checking its reliability and switching between the simple soft information calculation method which is known as the hard decision threshold (HDT) and traditional MAP method. Furthermore, the over-estimation of extracted soft information can reduce the performance of the system, therefore we introduce a scaling technique which can reduce the over-estimated values of the soft information and improve the error rate performance. Simulation results are produced to compare the performance of the proposed methods with the traditional.


MIMO, forward error correction, SIC-MMSE, JIDD, maximum a posteriori, hard decision threshold