TY - GEN
T1 - Channel Capacity Optimization Using MIMO Systems
T2 - 2nd IEEE International Conference on Electrical, Automation and Computer Engineering, ICEACE 2024
AU - Rong, Guozhi
AU - Yao, Rugui
AU - He, Yifeng
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, we investigate the application of MMSE algorithm to optimize the channel capacity in near-field super massive MIMO (Multiple-Input Multiple-Output) systems. Conventional MIMO systems also have problems such as poor spectral efficiency and high computational complexity, and this paper aims to optimize the spectral utilization efficiency, reduce the computational complexity, and realize the channel capacity optimization by using the MMSE algorithm. In the paper, the MMSE (Minimum Mean Square Error) algorithm is firstly designed on the basis of the traditional MMSE algorithm, combined with the orthogonal characteristics of the digital matrix, and through the idea of iterative correction; and then, based on the angular power spectral characteristics under the different application scenarios, the high-density antenna arrays are applied to the near-field ultra-large-scale MIMO system, and the antenna array geometries are realized and the optimization of the upper limit of channel capacity. Then, the paper implements the modelling of the channel by selecting the extended Saleh-Valenzuela channel model; finally, the effectiveness of the MMSE algorithm is also verified. Through the empirical study, it is found that when the number of RF links is 5 and the signal-to-noise ratio is 0 dB, the spectral efficiencies of this paper's algorithm are 36.71 bit/s/Hz and 51.77 bit/s/Hz, respectively; at this time, the spectral efficiencies of the traditional algorithm are 25.50 bit/s/Hz and 43.00 bit/s/Hz, respectively. Experiments have demonstrated that the algorithm in this paper has significant advantages in enhancing system capacity and transmission efficiency.
AB - In this paper, we investigate the application of MMSE algorithm to optimize the channel capacity in near-field super massive MIMO (Multiple-Input Multiple-Output) systems. Conventional MIMO systems also have problems such as poor spectral efficiency and high computational complexity, and this paper aims to optimize the spectral utilization efficiency, reduce the computational complexity, and realize the channel capacity optimization by using the MMSE algorithm. In the paper, the MMSE (Minimum Mean Square Error) algorithm is firstly designed on the basis of the traditional MMSE algorithm, combined with the orthogonal characteristics of the digital matrix, and through the idea of iterative correction; and then, based on the angular power spectral characteristics under the different application scenarios, the high-density antenna arrays are applied to the near-field ultra-large-scale MIMO system, and the antenna array geometries are realized and the optimization of the upper limit of channel capacity. Then, the paper implements the modelling of the channel by selecting the extended Saleh-Valenzuela channel model; finally, the effectiveness of the MMSE algorithm is also verified. Through the empirical study, it is found that when the number of RF links is 5 and the signal-to-noise ratio is 0 dB, the spectral efficiencies of this paper's algorithm are 36.71 bit/s/Hz and 51.77 bit/s/Hz, respectively; at this time, the spectral efficiencies of the traditional algorithm are 25.50 bit/s/Hz and 43.00 bit/s/Hz, respectively. Experiments have demonstrated that the algorithm in this paper has significant advantages in enhancing system capacity and transmission efficiency.
KW - Channel Capacity Optimization
KW - Complexity Analysis
KW - MIMO System
KW - MMSE Algorithm
KW - Near-field Ultra Large Scale
UR - http://www.scopus.com/inward/record.url?scp=105000792429&partnerID=8YFLogxK
U2 - 10.1109/ICEACE63551.2024.10898288
DO - 10.1109/ICEACE63551.2024.10898288
M3 - 会议稿件
AN - SCOPUS:105000792429
T3 - 2024 IEEE 2nd International Conference on Electrical, Automation and Computer Engineering, ICEACE 2024
SP - 80
EP - 86
BT - 2024 IEEE 2nd International Conference on Electrical, Automation and Computer Engineering, ICEACE 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 December 2024 through 31 December 2024
ER -