Dynamic Channel Models and Blockage

Large-scale propagation characteristics of mmWave frequencies have been heavily studied in recent years for coverage and interference analysis, but channel dynamics and the effects of human blockage have received less attention. MmWave signals are more susceptible to blockages than sub-6 GHz frequencies, partly due to reduced diffraction and the smaller wavelengths of higher frequencies that result in more diffuse scattering. Recent work has proven that diffraction is much less significant for common materials in indoor as compared to outdoor environments at 10, 20, and 26 GHz where signal attenuation was observed to be more than 20 dB in the deep shadow region. dy-channelIndoor human blockage measurements indicate rapid and deep signal attenuation by up to 40 dB or more when the blocker is close to either the TX or RX antenna with average fade durations of 200 to 300 ms with a human blocker moving at a pace of 1 m/s between the direct path between the TX and RX. Dynamic channel measurements were also conducted for a peer-to-peer outdoor scenario to study the effects of dynamic human blockage at mmWaves in a typical urban small-cell environment with large pedestrian crowds. Measurement data will be used to model blockage event characteristics such as rapid signal attenuation and the duration of blockage events. Such analysis will be vital for designing physical layer and higher layer protocols and frame structures for mmWave systems that will rely on the flexibility of rapid beam switching techniques to find secondary reflections and scatterers when a main cluster or reflection is blocked, in order to consistently maintain a mmWave link.


CitationResearch AreasDate
G. R. MacCartney, Jr. and T. S. Rappaport, “Rural Macrocell Path Loss Models for Millimeter Wave Wireless Communications,” in IEEE Journal on Selected Areas in Communications, vol. 35, no. 7, pp. 1663-1677, July 2017.100 GHz, Dynamic Channel Models, Macro-diversity, MmWave cellular system design, mmWave Channel Modeling, mmWave Channel Models, mmWave MAC, multi connectivity handover, Spatial Channel Estimation and Tracking, Spectrum Sharing2017/07/03
R. Ford, S. Rangan, E. Mellios, D. Kong and A. Nix, "Markov Channel-Based Performance Analysis for Millimeter Wave Mobile Networks," 2017 IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, CA, 2017, pp. 1-6. doi: 10.1109/WCNC.2017.7925768 Dynamic Channel Models, ns32017/06/01
G. R. MacCartney, Jr. and T. S. Rappaport, “A Flexible Wideband Millimeter-Wave Channel Sounder with Local Area and NLOS to LOS Transition Measurements,” in 2017 IEEE International Conference on Communications (ICC), Paris, France, May 2017, pp. 1-7.
View Presentation Slides
100 GHz, 5G Channel Models, Channel Sounder, Dynamic Channel Models, Macro-diversity, Millimeter Wave 5G Prototype, MmWave cellular system design, mmWave Channel Modeling, mmWave Channel Models, Prototyping and simulation software, Spatial Channel Estimation and Tracking2017/05/01
G. R. MacCartney, Jr. and T. S. Rappaport, “A Flexible Millimeter-Wave Channel Sounder with Absolute Timing,” IEEE Journal on Selected Areas in Communications, 2017. 100 GHz, Channel Sounder, Dynamic Channel Models, Macro-diversity2017/04/11
S. Deng, G. R. MacCartney Jr., T. S. Rappaport, “Indoor and Outdoor 5G Diffraction Measurements and Models at 10, 20, and 26 GHz,” 2016 IEEE Global Communications Conference (GLOBECOM), Washington, DC, 2016, pp. 1-7. doi: 10.1109/GLOCOM.2016.7841898100 GHz, Dynamic Channel Models, Millimeter Wave 5G Prototype, mmWave Channel Models2016/08/18
G. R. MacCartney Jr., S. Deng, S. Sun, T. S. Rappaport, “Millimeter-Wave Human Blockage at 73 GHz with a Simple Double Knife-Edge Diffraction Model and Extension for Directional Antennas,” to appear in the 2016 IEEE 84th Vehicular Technology Conference Fall (VTC 2016-Fall), Sept. 2016.Dynamic Channel Models, Macro-diversity2016/07/06
M. Giordani, M. Mezzavilla, A. Dhananjay, S. Rangan and M. Zorzi, "Channel Dynamics and SNR Tracking in Millimeter Wave Cellular Systems," European Wireless 2016; 22th European Wireless Conference, Oulu, Finland, 2016, pp. 1-8.Dynamic Channel Models, mmWave MAC2016/05/20
M. Zhang, M. Mezzavilla, R. Ford, S. Rangan, S. Panwar, E. Mellios, D. Kong, A. Nix, M. Zorzi, "Transport layer performance in 5G mmWave cellular", Computer Communications Workshops (INFOCOM WKSHPS) 2016 IEEE Conference on, pp. 730-735, 2016.Congestion Control, Dynamic Channel Models, ns32016/04/14
T. Lu, Pei Liu, S. Panwar, "Shining a Light into the Darkness: How Cooperative Relay Communication Mitigates Correlated Shadow Fading," 2015 IEEE 81st Vehicular Technology Conference (VTC Spring)Dynamic Channel Models2015/04/13
T. Lu, Pei Liu, S. Panwar "How long before I regain my signal," 2015 49th Conference on Information Sciences and Systems (CISS)Dynamic Channel Models2015/04/13


George R. MacCartney, Jr. and Theodore S. Rappaport