Allerton 2015 Paper Abstract


Paper ThC4.5

Ghods, Ramina (Cornell University), Jeon, Charles (Cornell University), Maleki, Arian (Columbia University), Studer, Christoph (Cornell University)

Optimal Large-MIMO Data Detection with Transmit Impairments

Scheduled for presentation during the Regular Session "Sensor Networks II" (ThC4), Thursday, October 1, 2015, 14:50−15:10, Pine

53rd Annual Allerton Conference on Communication, Control, and Computing, Sept 29-Oct 2, 2015, Allerton Park and Retreat Center, Monticello, IL, USA

This information is tentative and subject to change. Compiled on December 5, 2021

Keywords Wireless Communication Systems, Detection and Estimation, Multiuser Detection and Estimation


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.



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