Two-Stage Constant-Envelope Precoding for Low-Cost Massive MIMO Systems
Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with M ≫ 1 antennas requires M radio frequency (RF) chains with linear power amplifiers, which are very expensive. In this paper, we propose a two stage constant-envelop...
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Published in | IEEE transactions on signal processing Vol. 64; no. 2; pp. 485 - 494 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
IEEE
15.01.2016
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ISSN | 1053-587X 1941-0476 |
DOI | 10.1109/TSP.2015.2486749 |
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Abstract | Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with M ≫ 1 antennas requires M radio frequency (RF) chains with linear power amplifiers, which are very expensive. In this paper, we propose a two stage constant-envelope (CE) precoding scheme to enable low-cost implementation of massive MIMO BS with S ≪ M RF chains and nonlinear power amplifiers. Specifically, the MIMO precoder at the BS is partitioned into an RF precoder and a baseband precoder. The RF precoder is adaptive to the slow timescale channel statistics to achieve the array gain. The baseband precoder is adaptive to the fast timescale low dimensional effective channel to achieve the spatial multiplexing gain. Both the RF and baseband precoders are subject to CE constraints to reduce the implementation cost and the peak-to-average power ratio of the transmit signal. The two stage CE precoding is a challenging non-convex stochastic optimization problem and we propose an online alternating optimization algorithm which can autonomously converge to a stationary solution without explicit knowledge of channel statistics. Simulations show that the proposed solution has many advantages over various baselines. |
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AbstractList | Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with $M\gg1$ antennas requires $M$ radio frequency (RF) chains with linear power amplifiers, which are very expensive. In this paper, we propose a two stage constant-envelope (CE) precoding scheme to enable low-cost implementation of massive MIMO BS with $S\llM$ RF chains and nonlinear power amplifiers. Specifically, the MIMO precoder at the BS is partitioned into an RF precoder and a baseband precoder. The RF precoder is adaptive to the slow timescale channel statistics to achieve the array gain. The baseband precoder is adaptive to the fast timescale low dimensional effective channel to achieve the spatial multiplexing gain. Both the RF and baseband precoders are subject to CE constraints to reduce the implementation cost and the peak-to-average power ratio of the transmit signal. The two stage CE precoding is a challenging non-convex stochastic optimization problem and we propose an online alternating optimization algorithm which can autonomously converge to a stationary solution without explicit knowledge of channel statistics. Simulations show that the proposed solution has many advantages over various baselines. Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with M ≫ 1 antennas requires M radio frequency (RF) chains with linear power amplifiers, which are very expensive. In this paper, we propose a two stage constant-envelope (CE) precoding scheme to enable low-cost implementation of massive MIMO BS with S ≪ M RF chains and nonlinear power amplifiers. Specifically, the MIMO precoder at the BS is partitioned into an RF precoder and a baseband precoder. The RF precoder is adaptive to the slow timescale channel statistics to achieve the array gain. The baseband precoder is adaptive to the fast timescale low dimensional effective channel to achieve the spatial multiplexing gain. Both the RF and baseband precoders are subject to CE constraints to reduce the implementation cost and the peak-to-average power ratio of the transmit signal. The two stage CE precoding is a challenging non-convex stochastic optimization problem and we propose an online alternating optimization algorithm which can autonomously converge to a stationary solution without explicit knowledge of channel statistics. Simulations show that the proposed solution has many advantages over various baselines. |
Author | An Liu Lau, Vincent K. N. |
Author_xml | – sequence: 1 surname: An Liu fullname: An Liu email: eewendaol@ust.hk organization: Dept. of Electr. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China – sequence: 2 givenname: Vincent K. N. surname: Lau fullname: Lau, Vincent K. N. email: eeknlau@ece.ust.hk organization: Dept. of Electr. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China |
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Snippet | Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with M ≫ 1 antennas requires... Massive MIMO is a key technology to meet increasing capacity demands in 5G wireless systems. However, a base station (BS) equipped with $M\gg1$ antennas... |
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SubjectTerms | Antennas Arrays Baseband Channels Constant-envelope precoding Gain limited RF chains massive MIMO MIMO online alternating optimization Optimization PAPR Peak to average power ratio Power amplifiers Radio frequencies Radio frequency Statistics Time |
Title | Two-Stage Constant-Envelope Precoding for Low-Cost Massive MIMO Systems |
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