2021/03/13 by Brent A. Kenney, Kenney, Brent A., Arslan J. Majid +5
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #FOS: Electrical engineering #Signal Processing (eess.SP) #Wireless Communication Networks Research #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2103.07631
openalex publication_date 2021/03/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
By processing in the frequency domain (FD), massive MIMO systems can approach\nthe theoretical per-user capacity using a single carrier modulation (SCM)\nwaveform with a cyclic prefix. Minimum mean squared error (MMSE) detection and\nzero forcing (ZF) precoding have been shown to effectively cancel multi-user\ninterference while compensating for inter-symbol interference. In this paper,\nwe present a modified downlink precoding approach in the FD based on\nregularized zero forcing (RZF), which reuses the matrix inverses calculated as\npart of the FD MMSE uplink detection. By reusing these calculations, the\ncomputational complexity of the RZF precoder is drastically lowered, compared\nto the ZF precoder. Introduction of the regularization in RZF leads to a bias\nin the detected data symbols at the user terminals. We show this bias can be\nremoved by incorporating a scaling factor at the receiver. Furthermore, it is\nnoted that user powers have to be optimized to strike a balance between noise\nand interference seen at each user terminal. The resulting performance of the\nRZF precoder exceeds that of the ZF precoder for low and moderate input\nsignal-to-noise ratio (SNR) conditions, and performance is equal for high input\nSNR. These results are established and confirmed by analysis and simulation.\n