Mendeley TY _ JOUR ID - 13981211235686 TI - Low-Complexity Iterative Detection for Uplink Multiuser Large-Scale MIMO JO - Journal of Information Systems and Telecommunication (JIST) JA - ES LA - en SN - 2322-1437 AU - Amiri Mojtaba AU - Ferdosizade Naeiny Mahmoud AD - Shahed University AD - Shahed University Y1 - 2020 PY - 2020 VL - 29 IS - SP - 25 EP - 32 KW - Massive MIMO KW - KW - Iterative Method KW - KW - Matrix Inversion KW - KW - Maximum Likelihood KW - KW - MMSE Detection KW - DO - N2 - In massive Multiple Input Multiple Output (MIMO) or large scale MIMO systems, uplink detection at the Base Station (BS) is a challenging problem due to significant increase of the dimensions in comparison to ordinary MIMO systems. In this letter, a novel iterative method is proposed for detection of the transmitted symbols in uplink multiuser massive MIMO systems. Linear detection algorithms such as minimum-mean-square-error (MMSE) and zero-forcing (ZF), are able to achieve the performance of the near optimal detector, when the number of base station (BS) antennas is enough high. But the complexity of linear detectors in Massive MIMO systems is high due to the necessity of the calculation of the inverse of a large dimension matrix. In this paper, we address the problem of reducing the complexity of the MMSE detector for massive MIMO systems. The proposed method is based on Gram Schmidt algorithm, which improves the convergence speed and also provides better error rate than the alternative methods. It will be shown that the complexity order is reduced from O(〖n_t〗^3) to O(〖n_t〗^2), where n_t is the number of users. The proposed method avoids the direct computation of matrix inversion. Simulation results show that the proposed method improves the convergence speed and also it achieves the performance of MMSE detector with considerable lower computational complexity. UR - rimag.ir/en/Article/15446 L1 - rimag.ir/en/Article/Download/15446 ER -