Influence of Human Blocker in CDL Channel Model for 5G Millimeter Wave Communication

The millimeter wave (mm-wave) communication has emerged as a promising technology for future wireless networks, offering the potential for high-throughput during data transmission. However, the propagation of these high-frequency signals, as well as their vulnerability to blockage, pose significant challenges in creating accurate models of the mm-wave wireless channel. One approach to modeling these wireless channels is the Cluster Delay Line (CDL) concept, which captures the channel’s multipath propagation and time-varying nature using clustering fundamentals. In our paper, we propose a CDL-based wireless channel model that customizes cluster characteristics such as Delay Spread (DS), Angle Spread (AS), and power to statistically build the channel model for a specific indoor and outdoor scenario in the mm-wave band. Consideration of human blockers causes alteration in the cluster parameters and influences the performance of the 5G communication. Quality-of-Service (QoS) parameters, such as throughput and block error rate (BLER), is used to evaluate the model’s performance for the Enhanced Mobile Broadband (eMBB) use case of 5G. We construct a link budget both with and without human blockage, assessing the impact of blockage on cell coverage based on the performance of the block error rate. Using the 5G physical layer and simulation tools, the 5G performance is analyzed in terms of throughput under the influence of blockage. The contribution of base station density and self-blocking angle has also been analyzed regarding coverage probability. The results demonstrate how blockage and cluster parameters in the CDL channel are important while designing mm-wave communication system for 5G application.