Millimeter wave (mmWave) communication is a key technology for fifth generation (5G) and beyond communication networks. However, the communication quality of the radio link can be largely affected by rain attenuation, which should be carefully taken into consideration when calculating the link budget. In this paper, we present results of weather data collected with a PWS100 disdrometer and mmWave channel measurements at 25.84 GHz (K band) and 77.52 GHz (E band) using a custom-designed channel sounder. The rain statistics, including rain intensity, rain events, and rain drop size distribution (DSD) are investigated for one year. The rain attenuation is predicted using the DSD model with Mie scattering and from the model in ITU-R P.838-3. The distance factor in ITU-R P.530-17 is found to be inappropriate for a short-range link. The wet antenna effect is investigated and additional protection of the antenna radomes is demonstrated to reduce the wet antenna effect on the measured attenuation.

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. In this paper we present the architecture of the sounder and demonstrate its performance from back to back tests and from measurements of rms delay spread, path loss and MIMO capacity in an indoor and an outdoor environment. For 20 dB threshold, the rms delay spread for 90% of the measured locations is estimated at 1.4 ns and 1 ns for the indoor and outdoor environments, respectively. MIMO capacity close to the iid channel capacity for 2 by 2 configuration is achieved in both environments.

Large-scale fading models play an important role in estimating radio coverage, optimizing base station deployments and characterizing the radio environment to quantify the performance of wireless networks. In recent times, multi-frequency path loss models are attracting much interest due to their expected support for both sub-6 GHz and higher frequency bands in future wireless networks. Traditionally, linear multi-frequency path loss models like the ABG model have been considered, however such models lack accuracy. The path loss model based on a deep learning approach is an alternative method to traditional linear path loss models to overcome the time-consuming path loss parameters predictions based on the large dataset at new frequencies and new scenarios. In this paper, we proposed a feed-forward deep neural network (DNN) model to predict path loss of 13 different frequencies from 0.8 GHz to 70 GHz simultaneously in an urban and suburban environment in a non-line-of-sight (NLOS) scenario. We investigated a broad range of possible values for hyperparameters to search for the best set of ones to obtain the optimal architecture of the proposed DNN model. The results show that the proposed DNN-based path loss model improved mean square error (MSE) by about 6 dB and achieved higher prediction accuracy R2 compared to the multi-frequency ABG path loss model. The paper applies the XGBoost algorithm to evaluate the importance of the features for the proposed model and the related impact on the path loss prediction. In addition, the effect of hyperparameters, including activation function, number of hidden neurons in each layer, optimization algorithm, regularization factor, batch size, learning rate, and momentum, on the performance of the proposed model in terms of prediction error and prediction accuracy are also investigated.

High time resolution spectrum occupancy measurements and analysis are presented for 2.4 GHz WLAN signals. A custom-designed wideband sensing engine records the received power of signals, and its performance is presented to select the decision threshold required to define the channel state (busy/idle). Two sets of measurements are presented where data were collected using an omni-directional and directional antenna in an indoor environment. Statistics of the idle time windows in the 2.4 GHz WLAN are analyzed using a wider set of distributions, which require fewer parameters to compute and are more practical for implementation compared to the widely-used phase type or Gaussian mixture distributions. For the omni-directional antenna, it was found that the lognormal and gamma distributions can be used to model the behavior of the idle time windows under different network traffic loads. In addition, the measurements show that the low time resolution and angle of arrival affect the statistics of the idle time windows.

This paper presents a study which evaluated the potential for using ultra-low altitude, unmanned aerial vehicles to deliver fifth-generation (5G) cellular connectivity, particularly into areas requiring short-term enhancement in coverage. Such short-term enhancement requirements may include large gatherings of people or during disaster scenarios where there may be service outages or a need for increased bandwidth. An evaluation of this approach was conducted with empirically generated results regarding signal quality and cellular coverage-illustrating the potential of using unmanned ultra-low altitude aerial vehicles to deliver 5G cellular mobile services. Specifically, channel gain, mean time delay of the received signals (τ mean), and the root-mean-square spread of the delay (τ rms) were investigated for two distinct user modes at three different drone heights for three selected environments-an open area (field), a tree-lined environment, and an enclosed area. Maximum likelihood estimates for the various drone heights, user modes, and operational environments were found to be Rician distributed for the received signal strength measurements, whereas τ mean and τ rms for the open and tree-lined environments were Weibull distributed with the enclosed area tests being lognormally distributed. The paper also investigates how the channel gain may be affected when operating in each of the various global bands allocated for mid-5G communications, namely, Europe, China, Japan, South Korea, and North America. These regional mid-5G band allocations were found to yield minimal variance for all the environments considered.

No abstract

The International Telecommunications Union Radiocommunication Sector (ITU-R) StudyGroup 3 identified the need for a number of radio channel models in anticipation of the World Radiocommunications Conference in 2019 when the frequency allocation for 5G will be discussed. In response to the call for propagation path loss models, members of the study group carried out measurements in the frequency bands between 0.8 GHz up to 73 GHz in urban low-rise and urban high-rise as well as suburban environments. The data were subsequently merged to generate site general path loss models. The paper presents an overview of the radio channel measurements, the measured environments, the data analysis, and the approach for the derivation of the path loss model adopted in Recommendation ITU-R P.1411-10 (2019-08). Plain Language SummaryWireless communication networks require the estimation of the attenuation suffered by radio signals as they propagate between the transmitter and receiver in different environments. The International Telecommunications Union recommendation sector (ITU-R) provides models that can be used by network planners to guide the installation of base stations. The paper presents an overview of the model adopted in the recommendation ITU-R, P. 1411-10.

any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.