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Journal articles on the topic 'Spatially correlated MIMO channels'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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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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11

Nguyen, Vu, Hoang D. Tuan, Ha H. Nguyen, and Nguyen N. Tran. "Optimal Superimposed Training Design for Spatially Correlated Fading MIMO Channels." IEEE Transactions on Wireless Communications 7, no. 8 (2008): 3206–17. http://dx.doi.org/10.1109/twc.2008.070250.

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12

Chiani, M., M. Z. Win, and A. Zanella. "On the capacity of spatially correlated mimo rayleigh-fading channels." IEEE Transactions on Information Theory 49, no. 10 (2003): 2363–71. http://dx.doi.org/10.1109/tit.2003.817437.

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13

Il-Min Kim. "Exact BER analysis of OSTBCs in spatially correlated MIMO channels." IEEE Transactions on Communications 54, no. 8 (2006): 1365–73. http://dx.doi.org/10.1109/tcomm.2006.878823.

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14

Byers, G. J., and F. Takawira. "Spatially and Temporally Correlated MIMO Channels: Modeling and Capacity Analysis." IEEE Transactions on Vehicular Technology 53, no. 3 (2004): 634–43. http://dx.doi.org/10.1109/tvt.2004.825766.

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15

Nordin, Rosdiadee. "An Investigation of Self-Interference Reduction Strategy in a Spatially Correlated MIMO Channel." Journal of Computer Networks and Communications 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/424037.

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One of the efficient ways to transmit high data rate is by employing a multiple-input multiple-output (MIMO) transmission. One of the MIMO schemes, known as spatial multiplexing (SM), relies on the linear independence data streams from different transmit antennas to exploit the capacity from the fading channels. Consequently, SM suffers from the effect of spatial correlation which is the limiting factor in achieving the capacity benefit that SM can offer. In an attempt to increase the robustness of the SM transmission in a wide range of correlated channels, the use of dynamic subcarrier allocation (DSA) is investigated. The effective signal-to-interference-and-noise ratio (SINR) metric is used as the performance metric to determine the subcarrier quality which can then be utilised in the allocation. Two novel variants of the subcarrier allocation scheme are proposed. It is shown that the DSA-SINR approach improves the BER performance of SM transmission in highly correlated channels environment.

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16

Yuan, Fang. "Limited Feedback Strategy For MU-MIMO Systems Under Spatially Correlated Channels." Wireless Personal Communications 96, no. 3 (2017): 4279–97. http://dx.doi.org/10.1007/s11277-017-4386-x.

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17

Xu, Jindan, Wei Xu, Fengkui Gong, Hua Zhang, and Xiaohu You. "Optimal Multiuser Loading in Quantized Massive MIMO Under Spatially Correlated Channels." IEEE Transactions on Vehicular Technology 68, no. 2 (2019): 1459–71. http://dx.doi.org/10.1109/tvt.2018.2886346.

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18

Molisch, A. F., and X. Zhang. "FFT-Based Hybrid Antenna Selection Schemes for Spatially Correlated MIMO Channels." IEEE Communications Letters 8, no. 1 (2004): 36–38. http://dx.doi.org/10.1109/lcomm.2003.822512.

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19

Tran, N. N., and H. X. Nguyen. "Optimal SP training for spatially correlated MIMO channels under coloured noises." Electronics Letters 51, no. 3 (2015): 247–49. http://dx.doi.org/10.1049/el.2014.3607.

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20

Kafle, P. L., A. B. Sesay, and J. McRory. "Capacity of MIMO–OFDM systems in spatially correlated indoor fading channels." IET Communications 1, no. 3 (2007): 514. http://dx.doi.org/10.1049/iet-com:20045040.

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21

Barbero, L. G., and J. S. Thompson. "Performance of the complex sphere decoder in spatially correlated MIMO channels." IET Communications 1, no. 1 (2007): 122. http://dx.doi.org/10.1049/iet-com:20050414.

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22

Kontaxis, D. E., G. V. Tsoulos, G. E. Athanasiadou, and S. Karaboyas. "Optimality of Transmit Beamforming in Spatially Correlated MIMO Rician Fading Channels." Wireless Personal Communications 88, no. 2 (2015): 371–84. http://dx.doi.org/10.1007/s11277-015-3125-4.

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23

Forenza, Antonio, Matthew R. McKay, Ashish Pandharipande, Robert W. Heath, and Iain B. Collings. "Adaptive MIMO Transmission for Exploiting the Capacity of Spatially Correlated Channels." IEEE Transactions on Vehicular Technology 56, no. 2 (2007): 619–30. http://dx.doi.org/10.1109/tvt.2007.891427.

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24

N. Tran, Nguyen, and Ha X. Nguyen. "Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise." Journal of Science and Technology: Issue on Information and Communications Technology 1 (August 31, 2015): 41. http://dx.doi.org/10.31130/jst.2015.10.

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A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

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25

YANG, QINGHAI, and KYUNG SUP KWAK. "OPTIMAL TRAINING DESIGN FOR MIMO–OFDM SYSTEMS UNDER SPATIALLY CORRELATED DOUBLY SELECTIVE FADING CHANNELS." Journal of Circuits, Systems and Computers 16, no. 05 (2007): 673–97. http://dx.doi.org/10.1142/s0218126607003988.

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In this paper, we design an optimal training scheme for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems under spatially correlated time- and frequency- (doubly) selective fading channels. We first develop the optimal pilot symbols and placement of pilot clusters with respect to the minimum mean square error (MMSE) of the linear channel estimate. We then derive the optimal power allocation for pilot symbols in a two-water-level way: by maximizing the averaged capacity lower bound, how much power to be allocated for training is determined subject to the global water level (or the constraint of total transmit power); subsequently, pouring power to the pilot symbols with an approximately optimal water-filling scheme subject to the local water level (or the constraint of assigned power for training). In addition, for a particular OFDM size, the optimal number of pilot clusters is derived by maximizing the capacity lower bound and by minimizing the channel estimate's MMSE.

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26

Varghese, B. B., and B. T. Maharaj. "Modelling of a Spatially Correlated MIMO Wireless Channel." SAIEE Africa Research Journal 100, no. 1 (2009): 24–31. http://dx.doi.org/10.23919/saiee.2009.8531638.

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27

Ding, Qingfeng, and Yichong Lian. "Performance Analysis of Mixed-ADC Massive MIMO Systems Over Spatially Correlated Channels." IEEE Access 7 (2019): 6842–52. http://dx.doi.org/10.1109/access.2018.2889878.

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28

You, Li, Xiqi Gao, Xiang-Gen Xia, Ni Ma, and Yan Peng. "Pilot Reuse for Massive MIMO Transmission over Spatially Correlated Rayleigh Fading Channels." IEEE Transactions on Wireless Communications 14, no. 6 (2015): 3352–66. http://dx.doi.org/10.1109/twc.2015.2404839.

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29

Clerckx, Bruno, Claude Oestges, Luc Vandendorpe, Danielle Vanhoenacker-Janvier, and Arogyaswami J. Paulraj. "Design and Performance of Space–Time Codes for Spatially Correlated MIMO Channels." IEEE Transactions on Communications 55, no. 1 (2007): 64–68. http://dx.doi.org/10.1109/tcomm.2006.885063.

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30

Li, Feiyu, Yong Zuo, Ang Li, Zhihua Du, and Jian Wu. "Spatially correlated MIMO for exploiting the capacity of NLOS ultraviolet turbulent channels." Optics Express 27, no. 21 (2019): 30639. http://dx.doi.org/10.1364/oe.27.030639.

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31

Ramanathan, Ramachandran, and Madaswamy Jayakumar. "A novel cuckoo search approach to detection in spatially correlated MIMO channels." International Journal of Mathematical Modelling and Numerical Optimisation 6, no. 2 (2015): 101. http://dx.doi.org/10.1504/ijmmno.2015.069965.

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32

Mirhosseini, FahimeSadat, Aliakbar Tadaion, and S. Mohammad Razavizadeh. "Spectral Efficiency of Dense Multicell Massive MIMO Networks in Spatially Correlated Channels." IEEE Transactions on Vehicular Technology 70, no. 2 (2021): 1307–16. http://dx.doi.org/10.1109/tvt.2021.3050527.

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33

Hui Tong and S. A. Zekavat. "Spatially correlated MIMO channel: generation via virtual channel representation." IEEE Communications Letters 10, no. 5 (2006): 332–34. http://dx.doi.org/10.1109/lcomm.2006.1633313.

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34

Van Chien, Trinh, Christopher Mollen, and Emil Bjornson. "Large-Scale-Fading Decoding in Cellular Massive MIMO Systems With Spatially Correlated Channels." IEEE Transactions on Communications 67, no. 4 (2019): 2746–62. http://dx.doi.org/10.1109/tcomm.2018.2889090.

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35

Chen, J., Z. Du, and X. Gao. "Approximate capacity of OSTBC-OFDM in spatially correlated MIMO Nakagami-m fading channels." Electronics Letters 44, no. 8 (2008): 534. http://dx.doi.org/10.1049/el:20080171.

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36

Nan Zhang and B. Vojcic. "The performance of multiuser diversity scheduling for MIMO channels with spatially correlated fading." IEEE Transactions on Communications 54, no. 9 (2006): 1533–35. http://dx.doi.org/10.1109/tcomm.2006.881201.

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37

Barbero, L. G., and J. S. Thompson. "Erratum for ‘Performance of the complex sphere decoder in spatially correlated MIMO channels’." IET Communications 1, no. 2 (2007): 288. http://dx.doi.org/10.1049/iet-com:20079012.

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38

Recioui, A., and H. Bentarzi. "Genetic Algorithm Based MIMO Capacity Enhancement in Spatially Correlated Channels Including Mutual Coupling." Wireless Personal Communications 63, no. 3 (2010): 689–701. http://dx.doi.org/10.1007/s11277-010-0159-5.

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39

Yang, L., D. Tang, and J. Qin. "Performance of spatially correlated MIMO channel with antenna selection." Electronics Letters 40, no. 20 (2004): 1281. http://dx.doi.org/10.1049/el:20045802.

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40

Maharaj, B. T., and L. P. Linde. "Geometric modelling of a spatially correlated mimo fading channel." SAIEE Africa Research Journal 97, no. 2 (2006): 191–97. http://dx.doi.org/10.23919/saiee.2006.9488010.

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41

Sagar, Patel, and Bhalani Jaymin. "Near Optimal Receive Antenna Selection Scheme for MIMO System under Spatially Correlated Channel." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3732. http://dx.doi.org/10.11591/ijece.v8i5.pp3732-3739.

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Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations in MIMO systems under spatially correlated channel at transmit and receive antenna compare with several existing receive antenna selection schemes. The performance of proposed receive antenna selection scheme is same as conventional scheme and beat all other existing schemes.

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42

Kim, Wonsop, Kyungnam Lee, Myung-Don Kim, Jae Joon Park, Hyun Kyu Chung, and Hyuckjae Lee. "Performance Analysis of Spatially Correlated MIMO-OFDM Beamforming Systems with the Maximum Eigenvalue Model from Measured MIMO Channels." IEEE Transactions on Wireless Communications 11, no. 10 (2012): 3744–53. http://dx.doi.org/10.1109/twc.2012.083012.120164.

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43

LEE, In-Ho, Joong-Hoo PARK, and Dongwoo KIM. "Outage Performance of Multi-Hop Decouple-and-Forward Relaying in Spatially Correlated MIMO Channels." IEICE Transactions on Communications E93-B, no. 5 (2010): 1298–301. http://dx.doi.org/10.1587/transcom.e93.b.1298.

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44

Mckay, Matthew, and Iain Collings. "Error Performance of MIMO-BICM with Zero-Forcing Receivers in Spatially-Correlated Rayleigh Channels." IEEE Transactions on Wireless Communications 6, no. 3 (2007): 787–92. http://dx.doi.org/10.1109/twc.2006.05259.

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45

Dong, Peihao, Hua Zhang, Wei Xu, Geoffrey Ye Li, and Xiaohu You. "Performance Analysis of Multiuser Massive MIMO With Spatially Correlated Channels Using Low-Precision ADC." IEEE Communications Letters 22, no. 1 (2018): 205–8. http://dx.doi.org/10.1109/lcomm.2017.2761378.

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46

Palomar, D. P., and M. A. Lagunas. "Joint transmit-receive space-time equalization in spatially correlated MIMO channels: A beamforming approach." IEEE Journal on Selected Areas in Communications 21, no. 5 (2003): 730–43. http://dx.doi.org/10.1109/jsac.2003.810324.

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47

Qiu, Jiahua, Kui Xu, Xiaochen Xia, Zhexian Shen, and Wei Xie. "Downlink Power Optimization for Cell-Free Massive MIMO Over Spatially Correlated Rayleigh Fading Channels." IEEE Access 8 (2020): 56214–27. http://dx.doi.org/10.1109/access.2020.2981967.

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48

Zhemin Xu, S. Sfar, and R. S. Blum. "Analysis of MIMO Systems With Receive Antenna Selection in Spatially Correlated Rayleigh Fading Channels." IEEE Transactions on Vehicular Technology 58, no. 1 (2009): 251–62. http://dx.doi.org/10.1109/tvt.2008.923672.

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49

Fatani, Imade, Marie Zwingelstein-Colin, Mohamed Gharbi, François-Xavier Coudoux, Marion Berbineau, and Marc Gazalet. "An SVD-Aided Efficient Bit-Loading Algorithm for MIMO Transmission Over Spatially Correlated Channels." Wireless Personal Communications 75, no. 2 (2013): 1167–85. http://dx.doi.org/10.1007/s11277-013-1414-3.

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50

CHOI, J. W., and Y. H. LEE. "Complexity-Reduced Channel Estimation in Spatially Correlated MIMO-OFDM Systems." IEICE Transactions on Communications E90-B, no. 9 (2007): 2609–12. http://dx.doi.org/10.1093/ietcom/e90-b.9.2609.

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