Small-Scale, Local Area, and Transitional Millimeter Wave Propagation for 5G Communications

Abstract

This paper studies radio propagation mechanisms that impact handoffs, air interface design, beam steering, and MIMO for 5G mobile communication systems. Knife edge diffraction (KED) and a creeping wave linear model are shown to predict diffraction loss around typical building objects from 10 to 26 GHz, and human blockage measurements at 73 GHz are shown to fit a double knifeedge diffraction (DKED) model which incorporates antenna gains. Small-scale spatial fading of millimeter wave received signal voltage amplitude is generally Ricean-distributed for both omnidirectional and directional receive antenna patterns under both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions in most cases, although the log-normal distribution fits measured data better for the omnidirectional receive antenna pattern in the NLOS environment. Small-scale spatial autocorrelations of received voltage amplitudes are shown to fit sinusoidal exponential and exponential functions for LOS and NLOS environments, respectively, with small decorrelation distances of 0.27 cm to 13.6 cm (smaller than the size of a handset) that are favorable for spatial multiplexing. Local area measurements using cluster and route scenarios show how the received signal changes as the mobile moves and transitions from LOS to NLOS locations, with reasonably stationary signal levels within clusters. Wideband mmWave power levels are shown to fade from 0.4 dB/ms to 40 dB/s, depending on travel speed and surroundings.

Empirical Effects of Dynamic Human-Body Blockage in 60 GHz Communications

“…More recently, with the increasing interest in mmWave for 5G there have been a growing number of contributions that targeted other frequencies, such as 28 and 73 GHz. The authors of [5] reported a series of measurements performed with a single-input single-output (SISO) channel sounder operating at 73 GHz. Two horn antennas were pointed directly at each other to yield a channel that was dominated by a single LOS component, where a human blocker walked through the link at varying distances between the transmitter (TX) and the receiver (RX).…”

Millimeter-Wave Extended NYUSIM Channel Model for Spatial Consistency

“…A power delay profile (PDP) was recorded at each RX azimuth pointing angle, and the measurements at each location resulted in at most 120 PDPs (some angles did not have a detectable signal above the noise floor). The best RX pointing angle (the direction where the RX got the maximum received power) in the azimuth plane was selected as the starting direction for the RX azimuth sweeps (elevation remained fixed for all RXs), at each RX location measured [18].…”

“…24 directional PDPs (HPBW step increments in the azimuth plane, 360/15 = 24) [18] of one sweep at each location were combined to form one omnidirectional PDP to better illustrate spatial consistency. The denoising was done before this synthesis with a threshold of 20 dB below the peak power of each directional PDP.…”

“…Local area measurements were conducted in a street canyon at 73 GHz over a path length of 75 m, where the receiver moved from a non-line-of-sight (NLOS) environment to a line-ofsight (LOS) environment [18]. The measurements [18] provide a basis for the proposed model with spatial consistency. The NYUSIM channel model simulator operates over a wide range of carrier frequencies from 800 MHz to 100 GHz [1], [6], and provides temporal and 3-D spatial parameters for each MPC, and generates accurate CIRs, power delay profiles (PDPs) and 3-D angular power spectrums.…”

“…The spatial consistency extension proposed here allows the simulator to use additional parameters such as the velocity, location, and moving direction of a user to reproduce realistic CIRs received by the moving user with spatial consistency. This paper presents a modified channel coefficient generation procedure for spatial consistency under the framework of the NYUSIM channel model [2], and compares the simulation results with 73 GHz measured data from the street canyon measurements [18], and is organized as follows. Section II overviews existing models that consider spatial consistency, and provides current approaches for channel tracking.…”