Relevant bibliographies by topics / Spatially correlated MIMO channels

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Academic literature on the topic 'Spatially correlated MIMO channels'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Spatially correlated MIMO channels"

1

Raghavan, Vasanthan, Akbar M. Sayeed, and Venugopal V. Veeravalli. "Semiunitary Precoding for Spatially Correlated MIMO Channels." IEEE Transactions on Information Theory 57, no. 3 (2011): 1284–98. http://dx.doi.org/10.1109/tit.2010.2103810.

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2

Ozdogan, Ozgecan, Emil Bjornson, and Erik G. Larsson. "Massive MIMO With Spatially Correlated Rician Fading Channels." IEEE Transactions on Communications 67, no. 5 (2019): 3234–50. http://dx.doi.org/10.1109/tcomm.2019.2893221.

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3

Costa, Bruno Felipe, and Taufik Abrão. "MIMO Precoding for Correlated Fading Channels." Journal of Circuits, Systems and Computers 25, no. 05 (2016): 1650041. http://dx.doi.org/10.1142/s0218126616500419.

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This contribution proposes a precoder-decoder design aiming to improve the performance of multiple-input–multiple-output (MIMO) detectors under correlated fading channels. The MIMO detection principle namely minimum mean squared error (MMSE) detector is analyzed under such channel condition. The proposed approach deploys the channel state information (CSI) aiming to estimate the level of spatial correlation channel, namely normalized correlation index [Formula: see text] and uses this information to improve the MIMO system performance. Furthermore, the impact of the [Formula: see text] estimation errors on the performance, as well the performance degradation for different levels of correlation have been analyzed and compared with the classical MMSE-MIMO detector operating under uncorrelated channels and perfect channel estimation.
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4

Li, Guo Yan, and You Guang Zhang. "Efficient Antenna Selection in MIMO Correlated Channels." Advanced Materials Research 429 (January 2012): 242–48. http://dx.doi.org/10.4028/www.scientific.net/amr.429.242.

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Multiple-input multiple-output (MIMO) systems can bring many advantages to wireless communication but suffer from high cost and complexity due to the multiple RF chains. In such systems, antenna selection is introduced as a technique to ease these problems.This paper addressedthe problem of antenna selection in spatially correlated channels. We propose an effective antenna selection method in terms of capacity maximization based on the transmit and/or the receive correlation matrix instead of the instantaneous channel state information (ICSI).Simulations will be used to validate our analysis and demonstrate that the number of required RF chains can be significantly decreased using our low complexity algorithm whileachieving very close performance to the ICSI-based method.
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5

Pereira de Figueiredo, F. A., D. A. Mendes Lemes, C. Ferreira Dias, and G. Fraidenraich. "Massive MIMO channel estimation considering pilot contamination and spatially correlated channels." Electronics Letters 56, no. 8 (2020): 410–13. http://dx.doi.org/10.1049/el.2019.3899.

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6

Nordin, Rosdiadee. "Exploiting Spatial and Frequency Diversity in Spatially Correlated MU-MIMO Downlink Channels." Journal of Computer Networks and Communications 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/414796.

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The effect of self-interference due to the increase of spatial correlation in a MIMO channel has become one of the limiting factors towards the implementation of future network downlink transmissions. This paper aims to reduce the effect of self-interference in a downlink multiuser- (MU-) MIMO transmission by exploiting the available spatial and frequency diversity. The subcarrier allocation scheme can exploit the frequency diversity to determine the self-interference from the ESINR metric, while the spatial diversity can be exploited by introducing the partial feedback scheme, which offers knowledge of the channel condition to the base station and further reduces the effect before the allocation process takes place. The results have shown that the proposed downlink transmission scheme offers robust bit error rate (BER) performance, even when simulated in a fully correlated channel, without imposing higher feedback requirements on the base controller.
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7

Zhu, Yin, Chao Wang, Ping Wang, and Fu-qiang Liu. "A New PrecoderCodebook Design in Spatially Correlated MIMO Channels." Procedia Computer Science 92 (2016): 112–18. http://dx.doi.org/10.1016/j.procs.2016.07.331.

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8

McKay, M. R., and I. B. Collings. "General Capacity Bounds for Spatially Correlated Rician MIMO Channels." IEEE Transactions on Information Theory 51, no. 9 (2005): 3121–45. http://dx.doi.org/10.1109/tit.2005.853325.

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9

YU, Guangwei, and Xuzhen WANG. "Approximate Analysis of Power Offset over Spatially Correlated MIMO Channels." Communications and Network 01, no. 01 (2009): 25–34. http://dx.doi.org/10.4236/cn.2009.11004.

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10

Kim, Jin-Sung, Kyoung-Jae Lee, Haewook Park, and Inkyu Lee. "Transmission Mode Selection Algorithms for Spatially Correlated MIMO Interference Channels." IEEE Transactions on Signal Processing 60, no. 8 (2012): 4475–79. http://dx.doi.org/10.1109/tsp.2012.2198471.

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