Excited Markov Chain Monte Carlo MIMO detector with 8-antenna 802.11ac testbed demonstration

The development of low complexity, high performance spatial-multiplexing MIMO detectors continues to be an important area of research capable of increasing the spectral efficiency and capacity of wireless networks. The Markov Chain Monte Carlo (MCMC) detector has shown promise as a high performance...

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Bibliographic Details
Main Authors: Hedstrom, Jonathan C., Yuen, Chung Him George, Rong-Rong Chen, Farhang-Boroujeny, Behrouz
Format: Conference Proceeding
Language:English
Subjects:
Complexity theory
Detectors
MIMO
Monte Carlo methods
Quadrature amplitude modulation
Signal to noise ratio
Wireless communication
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Summary:The development of low complexity, high performance spatial-multiplexing MIMO detectors continues to be an important area of research capable of increasing the spectral efficiency and capacity of wireless networks. The Markov Chain Monte Carlo (MCMC) detector has shown promise as a high performance method with low complexity growth. We present a solution to the high SNR stalling problems of previous MCMC detectors. Near-MAP performance is verified in simulation and in real-world measurements on an 8-antenna MIMO testbed using the 802.11ac WiFi protocol. This demonstration shows that the channel models predominantly used in the MCMC literature are too well-conditioned to provide an understanding of performance and complexity for indoor channels. Additional information is provided on the methods and techniques to match simulation to measurement and to construct a low cost and effective 8-antenna MIMO testbed.
ISSN:1938-1883
DOI:10.1109/ICC.2017.7996951