The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste artigo, um algoritmo de pré-codificação não linear com baixa radiação fora de banda (OOB) é proposto para sistemas massivos de múltiplas entradas e múltiplas saídas (MIMO). O MIMO massivo configura mais de cem antenas em cada estação base para obter maior eficiência espectral e rendimento. O MIMO massivo totalmente digital pode restringir a resolução dos conversores digital para analógico (DACs), uma vez que cada DAC consome uma grande quantidade de energia. Em sistemas MIMO massivos com DACs de baixa resolução, métodos de projeto de sinais de saída de DAC por processamento não linear estão sendo investigados. O esquema convencional concentra-se apenas na taxa de soma ou nos erros nos sinais recebidos e, portanto, desencadeia uma grande radiação OOB. Este artigo propõe um critério de otimização que leva em consideração a potência da radiação OOB. A amostragem de Gibbs é usada como um algoritmo para encontrar soluções subótimas dado este critério. Os resultados numéricos obtidos através de simulação computacional mostram que o critério proposto reduz a potência média de radiação OOB por um fator de 10 em comparação com o critério convencional. O critério proposto também reduz a radiação OOB enquanto aumenta a taxa média de soma, otimizando o fator de peso para a radiação OOB. Como resultado, o critério proposto atinge taxas de soma média aproximadamente 1.3 vezes maiores do que um critério baseado em erro. Por outro lado, em comparação com um critério baseado na taxa de soma, o rendimento em cada subportadora apresenta menor variação, o que reduz o número de opções de adaptação de enlace necessárias, embora a taxa de soma média do critério proposto seja menor.
Taichi YAMAKADO
Keio University
Riki OKAWA
Keio University
Yukitoshi SANADA
Keio University
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Taichi YAMAKADO, Riki OKAWA, Yukitoshi SANADA, "Reduction of Out-of-Band Radiation with Quantized Precoding Using Gibbs Sampling in Massive MU-MIMO-OFDM" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 10, pp. 1240-1248, October 2022, doi: 10.1587/transcom.2021EBP3172.
Abstract: In this paper, a non-linear precoding algorithm with low out-of-band (OOB) radiation is proposed for massive multiple-input multiple-output (MIMO) systems. Massive MIMO sets more than one hundred antennas at each base station to achieve higher spectral efficiency and throughput. Full digital massive MIMO may constrain the resolution of digital-to-analog converters (DACs) since each DAC consumes a large amount of power. In massive MIMO systems with low resolution DACs, designing methods of DAC output signals by nonlinear processing are being investigated. The conventional scheme focuses only on a sum rate or errors in the received signals and so triggers large OOB radiation. This paper proposes an optimization criterion that takes OOB radiation power into account. Gibbs sampling is used as an algorithm to find sub-optimal solutions given this criterion. Numerical results obtained through computer simulation show that the proposed criterion reduces mean OOB radiation power by a factor of 10 as compared with the conventional criterion. The proposed criterion also reduces OOB radiation while increasing the average sum rate by optimizing the weight factor for the OOB radiation. As a result, the proposed criterion achieves approximately 1.3 times higher average sum rates than an error-based criterion. On the other hand, as compared with a sum rate based criterion, the throughput on each subcarrier shows less variation which reduces the number of link adaptation options needed although the average sum rate of the proposed criterion is smaller.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021EBP3172/_p
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@ARTICLE{e105-b_10_1240,
author={Taichi YAMAKADO, Riki OKAWA, Yukitoshi SANADA, },
journal={IEICE TRANSACTIONS on Communications},
title={Reduction of Out-of-Band Radiation with Quantized Precoding Using Gibbs Sampling in Massive MU-MIMO-OFDM},
year={2022},
volume={E105-B},
number={10},
pages={1240-1248},
abstract={In this paper, a non-linear precoding algorithm with low out-of-band (OOB) radiation is proposed for massive multiple-input multiple-output (MIMO) systems. Massive MIMO sets more than one hundred antennas at each base station to achieve higher spectral efficiency and throughput. Full digital massive MIMO may constrain the resolution of digital-to-analog converters (DACs) since each DAC consumes a large amount of power. In massive MIMO systems with low resolution DACs, designing methods of DAC output signals by nonlinear processing are being investigated. The conventional scheme focuses only on a sum rate or errors in the received signals and so triggers large OOB radiation. This paper proposes an optimization criterion that takes OOB radiation power into account. Gibbs sampling is used as an algorithm to find sub-optimal solutions given this criterion. Numerical results obtained through computer simulation show that the proposed criterion reduces mean OOB radiation power by a factor of 10 as compared with the conventional criterion. The proposed criterion also reduces OOB radiation while increasing the average sum rate by optimizing the weight factor for the OOB radiation. As a result, the proposed criterion achieves approximately 1.3 times higher average sum rates than an error-based criterion. On the other hand, as compared with a sum rate based criterion, the throughput on each subcarrier shows less variation which reduces the number of link adaptation options needed although the average sum rate of the proposed criterion is smaller.},
keywords={},
doi={10.1587/transcom.2021EBP3172},
ISSN={1745-1345},
month={October},}
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TY - JOUR
TI - Reduction of Out-of-Band Radiation with Quantized Precoding Using Gibbs Sampling in Massive MU-MIMO-OFDM
T2 - IEICE TRANSACTIONS on Communications
SP - 1240
EP - 1248
AU - Taichi YAMAKADO
AU - Riki OKAWA
AU - Yukitoshi SANADA
PY - 2022
DO - 10.1587/transcom.2021EBP3172
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2022
AB - In this paper, a non-linear precoding algorithm with low out-of-band (OOB) radiation is proposed for massive multiple-input multiple-output (MIMO) systems. Massive MIMO sets more than one hundred antennas at each base station to achieve higher spectral efficiency and throughput. Full digital massive MIMO may constrain the resolution of digital-to-analog converters (DACs) since each DAC consumes a large amount of power. In massive MIMO systems with low resolution DACs, designing methods of DAC output signals by nonlinear processing are being investigated. The conventional scheme focuses only on a sum rate or errors in the received signals and so triggers large OOB radiation. This paper proposes an optimization criterion that takes OOB radiation power into account. Gibbs sampling is used as an algorithm to find sub-optimal solutions given this criterion. Numerical results obtained through computer simulation show that the proposed criterion reduces mean OOB radiation power by a factor of 10 as compared with the conventional criterion. The proposed criterion also reduces OOB radiation while increasing the average sum rate by optimizing the weight factor for the OOB radiation. As a result, the proposed criterion achieves approximately 1.3 times higher average sum rates than an error-based criterion. On the other hand, as compared with a sum rate based criterion, the throughput on each subcarrier shows less variation which reduces the number of link adaptation options needed although the average sum rate of the proposed criterion is smaller.
ER -