An empirically based analysis of propagation characteristics in two vegetated suburban areas with different types and fractions of vegetation cover in 5G millimeter-wave bands is presented. A basic distance-dependent path loss model with a Gaussian random variance for shadow fading is utilized in accordance with the maximum-power directional and omnidirectional measurement data, therein exploiting significant path loss exponents in the presence of vegetation. In comparison with the existing ITU-R and 3GPP models, the effect of dense-leaved trees on path loss prediction is similar to that of buildings, whereas these standard models are inapplicable for sparse obstacle-line-of-sight (OLoS) links. Consequently, an azimuth-angle-based path loss characterization is proposed considering the antenna pattern, beam misalignment, and blockage effects. Moreover, several composite and cluster-level small-scale channel parameters, such as the number of clusters, delay spread, and angular spread, are extracted. Analysis of the first-arrival cluster in the OLoS setting reveals that forward scattering through foliage is still dominant and is expected to produce a larger azimuth angular spread of the arrival and compact multipath components in the time domain compared with line-of-sight and reflected clusters. Measurement results improve existing 3GPP channel models for suburban macrocell scenarios in millimeter-wave bands.

An empirically based analysis of propagation characteristics in two vegetated suburban areas with different types and fractions of vegetation cover in 5G millimeter-wave bands is presented. A basic distance-dependent path loss model with a Gaussian random variance for shadow fading is utilized in accordance with the maximum-power directional and omnidirectional measurement data, therein exploiting significant path loss exponents in the presence of vegetation. In comparison with the existing ITU-R and 3GPP models, the effect of dense-leaved trees on path loss prediction is similar to that of buildings, whereas these standard models are inapplicable for sparse obstacle-lineof-sight (OLoS) links. Consequently, an azimuth-angle-based path loss characterization is proposed considering the antenna pattern, beam misalignment, and blockage effects. Moreover, several composite and cluster-level small-scale channel parameters, such as the number of clusters, delay spread, and angular spread, are extracted. Analysis of the first-arrival cluster in the OLoS setting reveals that forward scattering through foliage is still dominant and is expected to produce a larger azimuth angular spread of the arrival and compact multipath components in the time domain compared with line-of-sight and reflected clusters. Measurement results improve existing 3GPP channel models for suburban macrocell scenarios in millimeter-wave bands.

No abstract

To progress cost-effective deployment of millimeter-wave (mmWave) wireless networks for indoor users, the prediction of indoor-to-indoor (I2I) and outdoor-to-indoor (O2I) coverage based on field measurement studies is of great interest to the future generation mobile communication system. First, measurements in I2I and O2I scenarios, which have advantages in terms of achieving a fair comparison of channel characteristics across different mmWave bands and bandwidths, are performed. Next, the developed dual-slope path loss model with a break-point distance is found to well fit omnidirectional and directional measured I2I data, especially at 39.5 GHz, revealing that the transition from lit or shadow regions to totally blocked regions is abrupt. Combined with space-time propagation characteristics, the indoor blockage effect on path loss and angular spread is investigated, therein being essential for the design of beam-steering and tracking algorithms. Double-directional measurement results show that most dominant paths arrive along the line-ofsight path, and only a few in-building reflections can be detected in higher frequency bands. Based on the joint analysis of channel measurement and modeling results, several mmWave network design and in-building coverage enhancement insights are presented.