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Massive MIMO Systems

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Signal Processing Techniques for Power Efficient Wireless Communication Systems

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

The development of massive multiple-input multiple-output (MaMIMO) techniques is motivated by the requirements of large spectral efficiency and reduced power consumption. The implementation of a large number of antennas offers a large spectral efficiency and link reliability. Moreover, the use of MaMIMO allows scaling down the transmitted power proportionally to the number of antennas used, which may lead to a significant improvement in terms of energy efficiency. Orthogonal frequency division multiplexing (OFDM) in combination with MaMIMO has a considerable potential to obtain very high data rates and high quality of service (QoS). However, MaMIMO systems require a mobile equipped with multiple antennas at the transmitter. This is a challenging issue in mobile devices mostly due to their size, cost, and computing power limitations. In MaMIMO, the radiated power per antenna decreases linearly with the number of antennas. Moreover, the effects of small-scale fading, non-coherent interference, and receiver noise are minimized. However, a massive number of antennas require a separate transceiver chain and power amplifier (PA) for each antenna (unless analog or hybrid analog-digital structures are used for beamforming purposes, in which case the number of RF chains can be reduced). In this situation, the size and costs of the analog front-end become a critical issue. The cost and size optimization implies the use of low-cost components which increase the imperfections that degrade the system performance. In this chapter, MaMIMO system performance, considering front-end RF imperfections and ADC/DAC with limited resolution, is carefully studied. Spectral and energy efficiency for the uplink and downlink scenarios are evaluated to quantify the overall system performance. Finally, low-resolution precoding techniques, antenna coupling, channel non-reciprocity, and channel estimation errors are also addressed.

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Authors and Affiliations

  1. Dpto. de Ing. Eléctrica y de Computadoras Universidad Nacional del Sur (UNS), Instituto de Inv. en Ing. Eléctrica “Alfredo Desages” (IIIE), UNS-CONICET, Bahía Blanca, Buenos Aires, Argentina

    Fernando Gregorio, Gustavo González, Christian Schmidt & Juan Cousseau

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  1. Fernando Gregorio
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  2. Gustavo González
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  4. Juan Cousseau
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Gregorio, F., González, G., Schmidt, C., Cousseau, J. (2020). Massive MIMO Systems. In: Signal Processing Techniques for Power Efficient Wireless Communication Systems. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-32437-7_8

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  • DOI: https://doi.org/10.1007/978-3-030-32437-7_8

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  • Print ISBN: 978-3-030-32436-0

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