Tropospheric attenuation prediction for future millimeter wave terrestrial systems: Estimating statistics and extremes.

Tropospheric attenuations can be significant in the millimeter wave (mmWave) frequency bands; hence, accurate prediction modeling of tropospheric attenuation is important for reliable mmWave communication. Several models have been established by the International Telecommunication Union (ITU), yet estimation accuracy is limited due to the large spatial scales used for model input parameters. In this paper, we address this and apply local precipitation data to analyze tropospheric attenuation statistics and compare to results when using ITU regional input rain data. Specifically, tropospheric attenuation is predicted via simulations using the ITU method at 30, 60, and 90 GHz in four distinct geographic locations with different climate types. From our simulations, we gather statistics for annual average rain attenuation, worst month rain attenuation, and rain attenuation per decade. Our results indicate that when using local measured rain data, for 1 km link distance, mean rain event attenuation increases from 0.5 to 2 dB. Local rain data yield larger attenuations at essentially all percentages of time not exceeded (essentially corresponding to all probability values): for example, for 0.1% of time not exceeded, in Columbia, SC, rain attenuation for 30 GHz frequency increases to 9 dB with local rain data, compared to 5 dB with ITU's regional data, corresponding to rain rates of 38.2 and 17.5 mm/h, respectively; at the same probability and location, the 90 GHz attenuation increases by 10 dB, from 10 to 20 dB when local rain data are used. Fog attenuations are also appreciable, reaching 8 dB for the 90 GHz frequency. Moreover, for the example locations, peak rain attenuations have increased at a rate of approximately 2 dB/decade over the past 50 years. Our results indicate that actual tropospheric attenuations may be substantially larger than that predicted by the ITU model when using regional rain rate data.

Threats from and Countermeasures for Unmanned Aerial and Underwater Vehicles.

The use of unmanned aerial vehicles (UAVs) for different applications has increased tremendously during the past decade. The small size, high maneuverability, ability to fly at predetermined coordinates, simple construction, and affordable price have made UAVs a popular choice for diverse aerial applications. However, the small size and the ability to fly close to the terrain make the detection and tracking of UAVs challenging. Similarly, unmanned underwater vehicles (UUVs) have revolutionized underwater operations. UUVs can accomplish numerous tasks that were not possible with manned underwater vehicles. In this survey paper, we provide features and capabilities expected from current and future UAVs and UUVs, and review potential challenges and threats due to use of such UAVs/UUVs. We also overview the countermeasures against such threats, including approaches for the detection, tracking, and classification of UAVs and UUVs.

Channel Prediction for mmWave Ground-to-Air Propagation under Blockage.

Ground-to-air (GA) communication using unmanned aerial vehicles (UAVs) has gained popularity in recent years and is expected to be part of 5G networks and beyond. However, the GA links are susceptible to frequent blockages at millimeter wave (mmWave) frequencies. During a link blockage, the channel information cannot be obtained reliably. In this work, we provide a novel method of channel prediction during the GA link blockage at 28 GHz. In our approach, the multipath components (MPCs) along a UAV flight trajectory are arranged into independent path bins based on the minimum Euclidean distance among the channel parameters of the MPCs. After the arrangement, the channel parameters of the MPCs in individual path bins are forecasted during the blockage. An autoregressive model is used for forecasting. The results obtained from ray tracing simulations indicate a close match between the actual and the predicted mmWave channel.

Ultra-Wideband Air-to-Ground Propagation Channel Characterization in an Open Area.

This paper studies the air-to-ground ultra-wideband channel through propagation measurements between 3.1 GHz to 4.8 GHz using unmanned-aerial-vehicles (UAVs). Different line-of-sight (LOS) and obstructed-LOS scenarios and two antenna orientations were used in the experiments. Multipath channel statistics for different propagation scenarios were obtained, and the Saleh-Valenzuela model was found to provide a good fit for the statistical channel model. An analytical path loss model based on antenna gains in the elevation plane is provided for unobstructed UAV hovering and moving (in a circular path) propagation scenarios.

Wireless localization for mmWave networks in urban environments.

Millimeter wave (mmWave) technology is expected to be a major component of 5G wireless networks. Ultra-wide bandwidths of mmWave signals and the possibility of utilizing large number of antennas at the transmitter and the receiver allow accurate identification of multipath components in temporal and angular domains, making mmWave systems advantageous for localization applications. In this paper, we analyze the performance of a two-step mmWave localization approach that can utilize time-of-arrival, angle-of-arrival, and angle-of-departure from multiple nodes in an urban environment with both line-of-sight (LOS) and non-LOS (NLOS) links. Networks with/without radio-environmental mapping (REM) are considered, where a network with REM is able to localize nearby scatterers. Estimation of a UE location is challenging due to large numbers of local optima in the likelihood function. To address this problem, a gradient-assisted particle filter (GAPF) estimator is proposed to accurately estimate a user equipment (UE) location as well as the locations of nearby scatterers. Monte-Carlo simulations show that the GAPF estimator performance matches the Cramer-Rao bound (CRB). The estimator is also used to create a REM. It is seen that significant localization gains can be achieved by increasing beam directionality or by utilizing REM.