An efficient paradigm for evaluating the channel capacity of closed-loop massive mimo systems

被引:0
作者
Al-Wahhamy A. [1 ]
Buris N.E. [2 ,3 ]
Al-Rizzo H. [1 ]
Yahya S. [1 ]
机构
[1] Systems Engineering Department, University of Arkansas at Little Rock, Little Rock, AR
[2] School of Communication and Information Engineering, Shanghai University, Shanghai
[3] Nebens, LLC (MIMObit Software), Chicago
关键词
Compendex;
D O I
10.2528/pierc19082806
中图分类号
学科分类号
摘要
A particular challenge encountered in designing massive MIMO systems is how to handle the enormous computational demands and complexity which necessitates developing a new highly efficient and accurate approach. Considering the large antenna array employed in the Base-Station (BS), in this work, we present a new paradigm to significantly reduce the simulation runtime and improve the computational efficiency of the combined rigorous simulations of the antenna array, 3-D channel model, and radiation patterns of the User Equipment (UE). We present an approach for evaluating a closed-loop massive MIMO channel capacity using 3-D beamforming to take advantage of spatial resources. The approach subdivides an M × N array at the BS into columns, rows, rectangular, or square subarrays, each consisting of a sub-group of antenna elements. The coupling is rigorously taken into account within each subarray; however, it is ignored among the subarrays. Results are demonstrated for a dual-polarized microstrip array with 128 ports. We consider simulation runtimes with respect to two different propagation environments and two different Signal-to-Noise-Ratios (SNRs). It is shown that the maximum difference in the closed-loop capacity evaluated using rigorous electromagnetic simulations and our proposed approach is 2.4% using the 2×(8×4) approach for both the 3-D Channel Model in the 3rd Generation Partnership Project (3GPP/3D) and the 3-D model in the independent and identically distributed (i.i.d/3D) model with a 46% reductional in computational resources compared with the full-wave antenna array modeling approach. © 2020, Electromagnetics Academy. All rights reserved.
引用
收藏
页码:1 / 16
页数:15
相关论文
共 42 条
[21]  
Ademaj F., Taranetz M., Rupp M., 3GPP 3D MIMO channel model: A holistic implementation guideline for open source simulation tools, Eurasipj.Wirel.Commun.Netw, 1, pp. 1-14, (2016)
[22]  
Tshibanda L., Et al., Neuroimaging after COMA, Neuroradiology, 52, 1, pp. 15-24, (2010)
[23]  
Song Y., Yun X., Nagata S., Chen L., Investigation on elevation beamforming for future LTE-advanced, 2013 IEEE International Conference on Communications Workshops (ICC), pp. 106-110
[24]  
Larsson E.G., Edfors O., Tufvesson F., Marzetta T.L., Massive MIMO for next generation wireless systems, IEEE Commun. Mag., 52, 2, pp. 186-195, (2014)
[25]  
Mondal B., Et al., 3D channel model in 3GPP, IEEE Commun. Mag, 53, 3, pp. 16-23, (2015)
[26]  
Nam Y., Et al., Full dimension MIMO for LTE-advanced and 5G, Information Theory and Applications Workshop (ITA), pp. 143-148, (2015)
[27]  
Lee W., Lee S.-R., Kong H.-B., Lee I., 3D beamforming designs for single user MISO systems, 2013 IEEE Global Communications Conference (GLOBECOM), pp. 3914-3919, (2013)
[28]  
Cheng X., Et al., Communicating in the real world: 3D MIMO, IEEE Wirel. Commun, 21, 4, pp. 136-144, (2014)
[29]  
Yu Y., Zhang J., Shafi M., Zhang M., Mirza J., Statistical characteristics of measured 3-dimensional MIMO channel for outdoor-to-indoor scenario in China and New Zealand, Chinese J. Eng, 2016, pp. 1-10, (2016)
[30]  
Thomas T.A., Nguyen H.C., Maccartney G.R., Rappaport T.S., 3D mmWave channel model proposal, IEEE Vehicular Technology Conference, (2014)