3D deterministic ray tracing method for massive MIMO channel modelling and parameters extraction. Issue 18 (29th October 2020)

• Record Type: Journal Article
• Authors: Liu, Gang; She, Jun; Lu, Wenjun; Zhang, Ming; Bo, Yaming
• Is Part Of: IET communications. Volume 14:Issue 18(2020)
• Page Start: 3169
• Page End: 3174
• Publication Date: 2020-10-29
• Subjects: radiowave propagation -- receiving antennas -- ray tracing -- MIMO communication -- antenna arrays -- stochastic processes; massive MIMO channel modelling -- parameters extraction -- geometric stochastic method -- massive multiple‐input multiple‐output channels -- high computational efficiency -- input parameters -- three‐dimensional deterministic ray tracing method -- conventional deterministic ray tracing methods -- geometric stochastic channel models -- receiving antenna array; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.0884
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Geometric stochastic method and deterministic ray tracing method are two common methods of modelling massive multiple‐input multiple‐output (MIMO) channels. The former has high computational efficiency but a large number of input parameters need to be extracted from measurements for different environments. Conversely, the latter is more suitable for a specific environment but consumes a lot of computing costs. In this study, a novel three‐dimensional (3D) deterministic ray tracing method for massive MIMO channel modelling is proposed. The computational efficiency can be improved in two aspects compared with conventional deterministic ray tracing methods. Firstly, substantial intersection tests used in determining the propagation paths of rays are replaced with the adjacency relationships between tetrahedrons. Secondly, the process of ray tracing is independent of the location of a receiving antenna and therefore repeated ray tracing process is unnecessary for different elements of receiving antenna array. The proposed method is also used as a substitute for measurements to extract input parameters for geometric stochastic channel models. The accuracy of the proposed method in massive MIMO channel modelling and parameters extraction is verified by comparing the results with measurements and other existing channel models.