Details

Autor(en) / Beteiligte

• Tan, Xiaosi
• Jin, Jiejun
• Sun, Kai
• Xu, Yunhao
• Li, Muhao
• Zhang, Yaping
• Zhang, Zaichen
• You, Xiaohu
• Zhang, Chuan

Titel

Enhanced Linear Iterative Detector for Massive Multiuser MIMO Uplink

Ist Teil von

• IEEE transactions on circuits and systems. I, Regular papers, 2020-02, Vol.67 (2), p.540-552

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2020

Quelle

IEEE

Beschreibungen/Notizen

• For massive multiuser multiple-input multiple-output (MIMO) systems, linear detectors, such as minimum mean square error (MMSE), suffer from unbearable computational pressure due to the large-scale matrix inversions. Various iterative detectors, such as Jacobi and steepest descent (SD) as well as their enhanced variants, are applied to improve the performance and complexity trade-off. However, their benefits would not maintain when: 1) the number of users is close to that of the base station antennas and 2) channel correlation is considered. To address this problem, an iterative detector based on SD and Barzilai-Borwein (BB) algorithms entitled SDBB is introduced in this paper. Furthermore, a novel enhanced SDBB (ESDBB) detector is proposed, which combines SDBB with SD to achieve better performance in the challenging scenarios. Both theoretical and numerical results are detailed to demonstrate the advantages of ESDBB in balancing the performance and complexity. Specifically, attaining faster convergence and better bit error rate (BER) results, ESDBB outperforms methods, including adaptive Jacobi and successive over relaxation (SOR). An efficient hardware architecture for the ESDBB detector is also proposed. Implementation results on a Xilinx Virtex-7 XC7VX690T FPGA show the advantages of the proposed ESDBB detector compared to the state of the art (SOA) in terms of throughput (31.3 Mb/s) and efficiency.