Research on Determinisitic Channel Capacity of MIMO System Based on Ray-Tracing Model in complex Indoor Environment
In this paper, the channel capacity is investigated as a crucial metric for evaluating the transmission capability of channel information, which is essential for the design and assessment of communication system performance. A deterministic channel model based on the reverse ray tracing method has been employed to establish a multi-input multi-output (MIMO) system in an indoor scenario. The multipath information of rays in the MIMO system under a deterministic channel was accurately calculated through the algorithm. The channel matrix was constructed using the data output by the algorithm, and the channel capacities of different MIMO systems in indoor scenarios were computed based on the MIMO system channel capacity formula. To verify the significance of MIMO systems in enhancing channel capacity, the channel capacities of single-input single-output (SISO), multi-input single-output (MISO), and MIMO systems, as well as MIMO systems with different numbers of antennas, were compared at different frequency points while keeping the horizontal distance of the transceiver antennas constant. Cumulative distribution function (CDF) graphs of each system were plotted, and the average capacity of each system was calculated. The results confirmed that MIMO systems can significantly improve the channel capacity of the system, and the average channel capacity increases with the order of the MIMO system. Additionally, various factors affecting the channel capacity of MIMO systems under deterministic channels, including frequency, line-of-sight (LOS) and non-line-of-sight (NLOS) propagation environments, and the number of antennas, were thoroughly discussed. The performance of MIMO systems was analyzed in terms of the singular values of the H matrix, the condition number of the channel matrix, and the correlation coefficients between antennas in the R normalized autocorrelation matrix, with the simulation results being explained and discussed.
Authors
- Lixin Guo (ORCID: https://orcid.org/0000-0003-3854-206X)
- Si-Yao Liu
- Zhongyu Liu (ORCID: https://orcid.org/0000-0002-2016-2424)
Institutions
- Xidian University (CN)
Publication Details
- Published
- 2024-10-23
- DOI
- https://doi.org/10.1109/isape62431.2024.10840562
- Primary Topic
- Telecommunications and Broadcasting Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00