Analytical Channel Modeling: From MIMO to Extra Large-Scale MIMO

TIAN Jiachen; HAN Yu; JIN Shi; ZHANG Jun; WANG Jue

doi:10.23919/cje.2023.00.418

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Jiachen TIAN, Yu HAN, Shi JIN, et al., “Analytical Channel Modeling: From MIMO to Extra Large-Scale MIMO,” Chinese Journal of Electronics, vol. 34, no. 1, pp. 1–15, 2025 doi: 10.23919/cje.2023.00.418

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Jiachen TIAN, Yu HAN, Shi JIN, et al., “Analytical Channel Modeling: From MIMO to Extra Large-Scale MIMO,” Chinese Journal of Electronics, vol. 34, no. 1, pp. 1–15, 2025 doi: 10.23919/cje.2023.00.418

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Analytical Channel Modeling: From MIMO to Extra Large-Scale MIMO

doi: 10.23919/cje.2023.00.418

TIAN Jiachen^1
,,
HAN Yu^{1
,
,},
JIN Shi^1
,,
ZHANG Jun^2
,,
WANG Jue^3
,

1.
National Mobile Communication Research Laboratory, Southeast University, Nanjing, 210096, China
2.
Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
3.
School of Information Science and Technology, Nantong University, 226019, China

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Author Bio:
Jiachen TIAN received the B.S. degree from Southeast University, Nanjing, China, in 2022. He is currently pursuing the Ph.D. degree at the School of Information Science and Engineering, Southeast University, Nanjing, China. His research interests include extra large-scale MIMO and reconfigurable intelligent surfaces. (Email: tianjiachen@seu.edu.cn)

Yu HAN received the B.S. degree in communications engineering from Hangzhou Dianzi University, Hangzhou, China, in 2012, and the M.S. and Ph.D. degrees in information and communications engineering from Southeast University, Nanjing, China, in 2015 and 2020, respectively. She was a Post-Doctoral Fellow with Singapore University of Technology and Design, Singapore, till 2020. She is currently an Associate Professor with Southeast University, Nanjing, China. Her research interests include extra large-scale MIMO and reconfigurable intelligent surface. Dr. Han and her coauthors have been awarded the IEEE Vehicular Technology Society 2023 Jack Neubauer Memorial Award. (Email: hanyu@seu.edu.cn)

Shi JIN received the B.S. degree in communications engineering from Guilin University of Electronic Technology, Guilin, China, in 1996, the M.S. degree from Nanjing University of Posts and Telecommunications, Nanjing, China, in 2003, and the Ph.D. degree in information and communications engineering from the Southeast University, Nanjing, in 2007. During June 2007 to October 2009, he was a Research Fellow with the Adastral Park Research Campus, University College London, London, UK He is currently with the faculty of the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China. His research interests include wireless communications, random matrix theory, and information theory. He is serving as an Area Editor for Transactions on Communications and IET Electronics Letters. He was an Associate Editor for IEEE Transactions on Wireless Communications, IEEE Communications Letters, and IET Communications. Dr. Jin and his coauthors have been awarded the 2011 IEEE Communications Society Stephen O. Rice Prize Paper Award in the field of communication theory, the IEEE Vehicular Technology Society 2023 Jack Neubauer Memorial Award, a 2022 Best Paper Award and a 2010 Young Author Best Paper Award by the IEEE Signal Processing Society. (Email: jinshi@seu.edu.cn)

Jun ZHANG received the M.S. degree in statistics and the Ph.D. degree in communications information system from Southeast University, Nanjing, China, in 2009 and 2013, respectively. During 2013 to 2015, he was a Postdoctoral Research Fellow with Singapore University of Technology and Design, Singapore. Since 2015, he has been with the faculty of the Jiangsu Key Laboratory of Wireless Communications, College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China, where he is currently a Professor. His research interests include massive MIMO communications, RIS-assisted wireless communications, UAV-assisted wireless communications, physical layer security, and large dimensional random matrix theory. Dr. Zhang was a recipient of the Globcom Best Paper Award in 2016, the IEEE APCC Best Paper Award in 2017, the IEEE JC&S Best Paper Award in 2022, the IEEE/CIC ICCC Best Paper Award in 2023, and the WCSP Best Paper Award in 2023. He has served as an Associate Editor for IEEE Communications Letters. (Email: zhangjun@njupt.edu.cn)

Jue WANG Dr. Wang has served as a Technical Program Committee member and a reviewer for a number of IEEE conferences/journals. He was awarded as an Exemplary Reviewer of IEEE Transactions on Communications in 2014, and Exemplary Reviewer of IEEE Wireless Communications Letters in 2021. His research interests include MIMO/Massive MIMO wireless communications, non-terrestrial networks, and machine learning in communication systems. (Email:wangjue@ntu.edu.cn)
Corresponding author: Email: hanyu@seu.edu.cn
Received Date: 2024-01-09
Accepted Date: 2024-03-28

Available Online: 2024-06-11

Abstract

Abstract

Multiple antenna technologies, from traditional multiple-input multiple-output (MIMO) to massive MIMO and the emerging extra large-scale MIMO, have consistently played a pivotal role in enhancing transmission rates by increasing the number of antennas. To guide the design of transmission strategies, channel models, especially analytical ones, are always significant tools, which can also reveal the performance improvements brought about by multiple antenna technologies. Analytical channel models have enjoyed significant success in traditional MIMO and massive MIMO systems. Nevertheless, due to the extended size of the array in an extra large-scale MIMO system, the distance between the receiver and the transmitter decreases and new channel properties, which did not manifest in massive MIMO systems, begin to kick in. To model the channel tailored for extra large-scale MIMO systems analytically, it is crucial to conduct a comprehensive review of traditional analytical MIMO channel models, which serves as a foundational step in understanding the fundamental characteristics of multi-antenna channels. In this paper, we first provide a survey on the state-of-the-art analytical MIMO channel models from the perspective of spatial correlation and signal propagation. Subsequently, we summarize the new properties of extra large-scale MIMO systems, i.e., near-field properties and spatial non-stationarities, and their influences on analytical channel modeling. Our objective is to elucidate how these novel properties affect the analytical MIMO channel models, and ultimately facilitate the development of precise analytical channel models well-suited to the extra large-scale MIMO systems.
- Extra large-scale MIMO,
- Massive MIMO,
- MIMO channel model,
- Near-field channel model,
- Spatial correlation

1Note that the VR discussed in this paper is different from the origin definition in channel models such as COST 2100 [17], in which the VR is defined as a geographic area. In other words, we only focus on the VR at the array side [6] in this paper.
2It has been verified in [41] that the correlation matrix of a UPA can be approximated as $ {\boldsymbol{\varTheta}}_X \approx {\boldsymbol{\varTheta}}_{X,h} \otimes {\boldsymbol{\varTheta}}_{X,v} $, $ X\in \{R,T \} $, where $ {\boldsymbol{\varTheta}}_{X,h} $ and $ {\boldsymbol{\varTheta}}_{X,v} $ are correlation matrices of the horizontal and vertical domains.
3Note that although the spatial non-stationarities and near-field properties have also been considered in massive MIMO systems [6], we introduce them together in the following section without distinguishing them in massive MIMO systems and extra large-scale MIMO systems.
4The distance terms in this paper are normalized by the wavelength then the $ \lambda $ in the denominator is omitted.

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References(93)

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