TY - GEN A1 - Tiwari, Krishan Kumar A1 - Grass, Eckhard A1 - Thompson, John S. A1 - Kraemer, Rolf T1 - Beam Entropy of 5G Cellular Millimetre-Wave Channels T2 - 90th IEEE Vehicular Technology Conference (VTC-Fall 2019), Honolulu, USA, 22 - 25 September 2019 N2 - In this paper, we obtain and study typical beam entropy values for millimetre-wave (mm-wave) channel models using the NYUSIM simulator for frequencies up to 100 GHz for the fifth generation (5G) and beyond 5G cellular communication systems. The beam entropy is used to quantify sparse MIMO channel randomness in beamspace. Lower relative beam entropy channels are suitable for memory- assisted statistically-ranked (MarS) and hybrid radio frequency (RF) beam training algorithms. High beam entropies can potentially be advantageous for low overhead secured radio communications by generating cryptographic keys based on the channel randomness in beamspace, especially for sparse multiple-input multiple- output (MIMO) channels. Urban microcell (UMi) and urban macrocell (UMa) cellular scenarios have been investigated in this work for 28, 60, 73, and 100 GHz carrier frequencies and the rural macrocell (RMa) scenario for 3.5 GHz. Y1 - 2019 SN - 978-1-7281-1220-6 SN - 978-1-7281-1219-0 SN - 978-1-7281-1221-3 U6 - https://doi.org/10.1109/VTCFall.2019.8891530 SN - 2577-2465 SN - 1090-3038 ER - TY - GEN A1 - Tiwari, Krishan Kumar A1 - Grass, Eckhard A1 - Thompson, John S. A1 - Kraemer, Rolf T1 - Memory-Assisted Statistically-Ranked RF Beam Training Algorithm for Sparse MIMO T2 - 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) Y1 - 2019 SN - 978-1-7281-5207-3 SN - 978-1-7281-4053-7 U6 - https://doi.org/10.1109/VTC2020-Spring48590.2020.9129037 SN - 2577-2465 SN - 1090-3038 ER -