Real-world transceiver designs for multiple-input multiple-output (MIMO) wireless communication systems are affected by a number of hardware impairments that already appear at the transmit side, such as amplifier non-linearities, quantization artifacts, and phase noise. While such transmit-side impairments are routinely ignored in the data-detection literature, they often limit reliable communication in practical systems. In this paper, we present a novel data-detection algorithm, referred to as large-MIMO approximate message passing with transmit impairments (short LAMA-I), which takes into account a broad range of transmit-side impairments in wireless systems with a large number of transmit and receive antennas. We provide conditions in the large-system limit for which LAMA-I achieves the error-rate performance of the individually-optimal (IO) data detector. We furthermore demonstrate that LAMA-I achieves near-IO performance at low computational complexity in realistic, finite dimensional large-MIMO systems.
@article{arxiv.1510.06097,
title = {Optimal Large-MIMO Data Detection with Transmit Impairments},
author = {Ramina Ghods and Charles Jeon and Arian Maleki and Christoph Studer},
journal= {arXiv preprint arXiv:1510.06097},
year = {2015}
}
Comments
Presented at the 53rd Annual Allerton Conference on Communication, Control, and Computing