Outdoor Propagation Research Articles

Development of Database Accessibility for Frequency Scheduling of TVWS Broadband Connectivity in Rural Areas Using Dynamic Spectrum Access Technique

As a result of the switchover from analogue to digital transmission, Television White Space (TVWS) presented itself as good opportunity to supplement the existing licensed spectrum to ease the spectrum scarcity. Rural communities were usually not connected due to poor returns to the internet providers to provide broadband access to the areas. This research has prepared the framework and feasibility study for deploying broadband internet services using Television White Space (TVWS) technology in Ugbawka, a rural area in Enugu state, Nigeria. In this work, a Network Ping was run on five websites using three major internet service providers as backhaul to establish facts of poor or even non-existent internet services. Using Ping Plotter 5 Pro, accessing ieee.com using MTN yielded a Round Trip (RT) average of 846.433 ms, with a loss of 83.8% packet over 10mins count. Radio Frequency (RF) Explorer and Carlson transceiver, Customer Premise Equipment (CPE) were used for field trials to determine availability of TVWS Frequencies. A database app was developed by writing some codes in the Basic for Android (B4A) Intermediate Development Environment (IDE). Empirical outdoor propagation model was developed with a 2.15 pathloss exponent while the indoor propagation model gave a pathloss exponent of 3.47 . An algorithm was developed, titled, TVWS Optimization Quadrature Amplitude Algorithm, (TOQA), where throughput of this project performed better by giving 60Mbps and 70 Mbps at Signal-Noise-Ratio (SNR) of 5dB while the conventional algorithm gave 30Mbps and 25 Mbps at same SNR value. The Bit Error Rate was lower than the conventional models used, giving the TOQA values of 10-3 at SNR of 5 dB and 10-6 at SNR of 30 dB while the conventional method gave 10-1 and 10-3 respectively at the same SNR values. With an Average of 56.2% network latency recorded in Ugbawka, TVWS will make a great impact on Internet connectivity if deployed.

S-shaped dependence of the sound pressure level in outdoor propagation on the effective sound speed gradient

The effective sound speed gradient is used to describe the meteorological conditions during sound measurements at roads and railways. Meteorological parameters were assessed up to a height of 10 m. The sound level differences between a reference point close to the passing vehicles and at distances of 100–500 m from motorways and railway tracks were determined. These differences were found to correlate well with the effective sound speed gradient determined from the measured temperature and wind speed gradients which follow the day/night cycle as a result of the reversing air temperature gradient, incoming solar radiation and wind conditions. The correlation with sound level differences can be approximated by an S-shaped function which is constant for large positive or negative gradients of the effective sound speed. These threshold values are a consequence of the local meteorological and attenuation conditions. The analysis shows that large effective sound speed gradients are mainly a result of the wind conditions whereas gradients without a substantial wind speed contribution are low and a result of the temperature gradient. In the distance range between 150 m and 250 m, the meteorological influences cause a level increase of 3–4 dB(A) for downward refracted sound rays (favourable sound propagation) compared to a situation without meteorological influence (effective sound speed gradient of zero). In the same distance range, meteorological conditions cause a maximum sound level attenuation of 5–10 dB(A) for upward curved sound rays (unfavourable sound propagation).

Relay Placement Algorithms for IoT Connectivity and Coverage in an Outdoor Heterogeneous Propagation Environment

A vast majority of the Internet of Things (IoT) devices will be connected in a topology where the edge-devices push data to a local gateway, which forwards the data to a cloud for further processing. In sizeable outdoor deployment regions, the edge-devices may experience poor connectivity due to their distant locations and limited transmission power. Repeaters or relays must be placed at a few locations to ensure reliable connectivity to either a gateway or another node in the network. A big challenge in achieving reliable connectivity and coverage is the outdoor propagation environment being heterogeneous. Engineers often deploy networks based on resource-intensive field visits, detailed surveys, measurements, initial test deployments, followed by fine-tuning. For scalability to large scale IoT deployments, automated network planning tools are essential. Such tools should predict connectivity based on the edge-device locations using available Geographical Information System (GIS) data, identify the need for relays/repeaters, and, if needed, suggest the number of relays needed with their locations. Furthermore, such tools should also be extended to suggest the minimum number and locations of base stations that maximise coverage. In this paper, we propose an automated network deployment framework using a black box received signal strength estimation oracle that provides signal strength estimates between candidate pairs of transceiver locations in a heterogeneous deployment region. Our proposed methodology uses either Ant Colony Optimisation (ACO) or Differential Evolution (DE) to identify the number and locations of relays for meeting specified quality of service constraints. We discuss adaptations of our techniques to handle scenarios with multiple gateways. Further, we show the effectiveness of these algorithms to find suitable candidate base station locations to provide coverage in a heterogeneous propagation environment that meets the specified quality of service constraints. We then demonstrate the effectiveness of our algorithms in two deployment regions.

Changes in the Soundscape of the Public Space Close to a Highway by a Noise Control Intervention

The deployment of measures to mitigate sound during propagation outdoors is most often a compromise between the acoustic design, practical limitations, and visual preferences regarding the landscape. The current study of a raised berm next to a highway shows a number of common issues like the impact of the limited length of the noise shielding device, initially non-dominant sounds becoming noticeable, local drops in efficiency when the barrier is not fully continuous, and overall limited abatement efficiencies. Detailed assessments of both the objective and subjective effect of the intervention, both before and after the intervention was deployed, using the same methodology, showed that especially the more noise sensitive persons benefit from the noise abatement. Reducing the highest exposure levels did not result anymore in a different perception compared to more noise insensitive persons. People do react to spatial variation in exposure and abatement efficiency. Although level reductions might not be excessive in many real-life complex multi-source situations, they do improve the perception of the acoustic environment in the public space.

Developing an Adaptive Channel Modelling using a Genetic Algorithm Technique to Enhance Aerial Vehicle-to-Everything Wireless Communications

In this digital era, Internet of Everything (IoE) has a potential to bring out drastic changes to how we live today, where billions of people and devices require wireless connectivity. Where Unmanned Aerial Vehicles contribute positively in paving the way for IoE and Fifth Generation technologies, and tackle some of their comms challenges. Thus, this paper aims to provide an adaptive approach using a Genetic Algorithm (GA) technique by combining indoor and outdoor propagation models to enhance aerial vehicle-to-everything wireless connectivity. The proposed adaptive approach uses a GA multi-objective function that yield optimum values of UAV altitude, elevation angles, and type of building for indoor environment. The proposed GA optimization technique has met the demand of a typical dense-populated urban environment, as well as empowering the IoE with greater coverage footprint, high Quality of Service benchmark, and line-of-sight adaptability. The output results emphasized that the proposed adaptive approach using the GA technique can help in smart decision-making and selecting a proper setup and find the optimum parameters to provide seamless wireless connections from aerial vehicle-to-everything.

Evaluation of Power Receiving Signal of 5G Small Cells for Outdoor/Indoor Environment at Millimeterwave Bands

This paper presents a simulation study of the outdoor and indoor propagation losses utilizing 5G small cells at suggested millimeter-wave frequencies of 26 GHz, 28 GHz, and 38 GHz. The environment of this study is conducted with penetration loss of new and old building characteristics. The simulation is performed with help of 3D ray tracing model NVIDIA OptiX engine and MATLAB. The targeted frequencies are 26 GHz, 28 GHz, and 38 GHz that specified by International Telecommunication Union ITU-R organization. The simulation routes are investigated in term of signal strength at multiple receiving points. The strength angular spectrum are represented for fixed points and the power receiving delay is presented by their attributes. The simulated responses showed an efficient and sufficient outdoor and indoor service might be provisioned at 26 GHz and 28 GHz. The received signals at 28 GHz and 38 GHz are found around 4.5 dB and 11 dB with comparison with signal received level at 26 GHz. However, at 38 GHz the indoor signal strength and power receiving delays demonstrate a weak signal reception which offers a poor solution to indoor user by outside fixed base station.

Analytical Explanation of Electromagnetic Diffraction From Double-layered Dielectric Wedge

This article explains the phenomenon of electromagnetic diffraction from a double-layered dielectric wedge analytically. Mountain ridges with forest or snow cover, concrete building with wooden interior wall decoration or vertical garden, et cetera are good examples of double-layered dielectric wedges that often appear in indoor and outdoor propagation channel models. The analytical model presented here considers the contributions from the inner and outer wedges individually. Then the total diffracted field is calculated by superimposing one upon another. The problem becomes complex because the field diffracted from the inner wedge has a cylindrical wavefront, which gets the chance to reach air only after transmitting through the outer wedge’s dielectric material. Moreover, since the interface between air and the outer wedge dielectric is not planar, it adds to the complexity of the problem. The proposed analytical model has been validated by comparing its results with the results from finite-difference time-domain (FDTD) simulations.

Review on Ray Tracing Channel Simulation Accuracy in Sub-6 GHz Outdoor Deployment Scenarios

In this article, a review of the achieved accuracy in the literature for ray tracing (RT) based channel modeling is presented with a focus on outdoor propagation scenarios in the sub-6 GHz frequency range. The achieved accuracy is analyzed from three perspectives: 1) The input parameters which include the environmental description in the form of digital maps and the corresponding constitutive material parameters; 2) from the interaction mechanisms perspective and 3) from the output perspective where the achieved accuracy of predicted path loss is reviewed. Uniform assignment of materials to the entire propagation scenario is observed in most of the works in the literature which is attributed to the composite nature of common building materials and the difficulty of characterizing all material properties especially for outdoor scenarios. The digital maps are shown to introduce a certain degree of uncertainty in the RT predictions as most common sources of the maps hardly publish the accuracy. Notwithstanding, the prediction of path loss in most RT tools is observed to be rather robust against the inaccuracies in the input parameters with most RT tools achieving a prediction accuracy with a mean error below 4 dB and a standard deviation (STD) below 8 dB.

Simplified Assessment on the Wind Farm Noise Impact of the E2O Experimental Offshore Station in the Asturian Coast

This paper presents a preliminary evaluation of the acoustic impact of an offshore experimental wind farm (E2O), conceived and planned to be installed in Asturias on Spain’s northwest coast. A simplified assessment of the wind turbines’ noise impact at an offshore platform was performed numerically, adapting commercial software for room acoustics to this particular application. As a result, the sound levels at specific receiver sites on the coastline were estimated to select the most convenient level between the two possible locations. Parameters from acoustic emission data of the selected wind turbines were introduced as inputs to the simulation, and the noise propagation in the analyzed domains (for different values of their basic parameters) was simulated. Complementarily, the numerical results were compared to calculations following the ISO 9613-2 standard on sound propagation outdoors for validation purposes, showing good overall agreement. The results revealed that both projected areas under consideration follow the current normative concerning the prescribed acoustic limits, according to the predicted low sound pressure values at the specific considered receiver sites.

Comparison of SNR and channel capacity with micro and milli-meter wave bands based on outdoor propagation measurement

Comparison of SNR and channel capacity with micro and milli-meter wave bands based on outdoor propagation measurement

Comparison of SoundPlan 4.0 noise modeling software and field noise measurements results at two different outdoor entertainment spaces (Glamping and Winery venues)

Evaluation of noise in outdoor entertainment spaces is a topic of interest in our communities . Noise from outdoor entertainment spaces has turned into an unwanted activity in rural communities due to high levels sound pressure from music events and crowd noise. There are numerous complaints from neighbors or neighborhood associations pertaining noise pollution around areas near these spaces. For this case study, field noise measurements were conducted in a winery for a regular concert season. Evaluation of the noise predictions using SoundPlan 4.0 for the winery venue and for a Glamping (“luxurious camping”) venue are the main focus of this study. The paper aims to determine a correlation between field noise measurements, methodology from ISO 9613-2:1996 Standard “Attenuation of sound during propagation outdoors,” and noise prediction results using SoundPlan 4.0 computer modeling software.

Near shore atmospheric acoustic transmission loss: Method and measurements

A model for moderate to long range outdoor propagation of sound in complex environments must account for a wide variety of parameters. Generally, the characteristics of the source, the space through which the sound propagates, and the receiver must all be considered. This larger project aims to understand atmospheric acoustic transmission loss in the littoral and riverine environments at ranges of up to approximately 3 km. In such an environment, some of the confounding factors in the propagation path include: wind speed and direction, temperature and humidity profiles, absorption, refraction, dispersion, turbulence, diffraction, dynamically changing water surface geometry, shore terrain geometry and surface impedance along the propagation path. A simple pitch-catch configuration with the source over water and the microphone arrays on shore is used to capture transmission loss information, along with concurrent meteorological measurements. In this work, the measurement system is described and preliminary results from measurements at three sites are reported. These measurements inform the concurrent effort to develop and validate an improved model for acoustic transmission loss in these scenarios.

Design of a very high frequency stretchable inverted conical helical antenna for maritime search and rescue applications

AbstractThe design of a stretchable inverted conical helical antenna (SICHA) applicable to maritime search and rescue is proposed, and the gain and the reflection coefficient are obtained at a resonant frequency of 156 MHz. The optimized top and bottom diameters of the SICHA are 36 and 18 mm, respectively, and its height is 115 mm, which is much shorter than a quarter‐wavelength monopole. Finally, we simulate the outdoor propagation of electromagnetic waves with the SICHA; both the simulated and measured received power intensities are similarly reduced as the distance between the two antennas increases.

Open-Source and Low-Cost Test Bed for Automated 5G Channel Measurement in mmWave Band

The fifth-generation cellular networks (5G) has been proposed as a solution for the accelerating growth in data traffic. As part of 5G, millimeter-wave (mmWave) is suggested as one of the potential spectrum candidates due to the vastly available bandwidth. Accordingly, both indoor and outdoor propagation measurements on mmWave have been widely conducted over the recent years. These field measurements were heavily dependent on utilizing expensive channel-sounders and tools. In this paper, we propose an affordable and open-source test-bed solution for mmWave channel modeling covering 24 and 77 GHz bands. The key contribution in the proposed test-bed is the use of cost-effective mmWave Doppler radars, a specific methodology is developed for this purpose. The proposed test-bed is capable of resolving the received power at any given combination of angles-of-arrival (AoA) and angles-of-departure (AoD). In order to verify the functionality of the proposed test bed, several measurement scenarios have been investigated in different indoor environments, the obtained propagation results using this test bed indicate a good consistency with the expected mmWave propagation characteristics. As the proposed test bed is an open source and cost-effective, researchers and RF designers can easily conduct mmWave propagation measurements according to their particular needs.

Channel estimation for 3D MIMO system based on LOS/NLOS identification

Channel estimation is one of the most important parts in three-dimensional multiple-input multiple-output (3D MIMO) systems. The characteristics of non-line-of-sight (NLOS) channel and line-of-sight (LOS) channel are different in 3D MIMO systems. If the same channel estimation scheme is used in LOS case as NLOS, the performance of estimation will be bad. In outdoor propagation environment, 3D MIMO channels between closely located antennas share the same delay support in temporal domain. With those prior knowledge, in this study, a new channel estimation scheme is proposed. The proposed scheme can be divided into two processes. First, it is needed to identify the received sounding reference signal whether is LOS or NLOS propagation. Then, different enhanced DFT-based channel estimation schemes are proposed separately according to the identification results. Simulation results verify the proposed algorithm outperforms traditional discrete Fourier transform (DFT)-based channel estimation. At signal-to-noise ratio of 20 dB, the proposed algorithm has 17.7 and 35.7% improvement in NLOS case and LOS case separately in terms of normalised mean squared error compared with traditional DFT-based channel estimation scheme, and is achieved with additional liner complexity.

Efficient Evaluation of Massive MIMO Channel Capacity

Massive multiple-input multiple-output (MIMO) is a key promising technology for 5G wireless networks that allows significant increase in spectral and energy efficiency without increasing the spectrum and/or the number of cell sites. However, the computational time and resources required to rigorously analyze the capacity offered by a base station (BS) equipped with a large number of antenna elements increase with the increase of the number of antenna elements in the array. In this paper, we present a novel approximation approach for modeling large microstrip antenna arrays in BSs of massive MIMO systems. The approach subdivides an M × N array into columns, rows, rectangular, or square subarrays, each consisting of a group of elements. The coupling is rigorously taken into account within each subarray, but it is ignored between subarrays, using just an array factor instead. Results are demonstrated for an 8 × 8 = 64 element patch array. It is shown that the difference in the capacity evaluated using rigorous electromagnetic simulations and the proposed approach is less than 0.79% using the 2 × (8 × 4) approach for both the suburban macrocell model of the Extended Spatial Channel Model (SCME/suburban macro cell (SMa)) outdoor propagation model and three-dimensional independent identically distributed model with a significant reduction of 44% and 50%, respectively, in computational time as compared to the full-wave antenna array modeling approach.

An outdoor sound propagation model in concert with geographic information system software

As industrial technology advances, man-made noise has increasingly contributed to natural environment soundscapes. To predict how this anthropogenic noise can affect these natural environments, engineers build acoustic models over given terrain; however many current models are not compatible with common Geographic Information System (GIS) software, could become outdated due to software version updates, or are written as proprietary packages unavailable to park management. The goal of this study was to create a true open source outdoor sound propagation model compatible with (but not dependent on) outside GIS software. The model was developed to include uneven terrain, atmospheric absorption, screening, wind effects, and ground effects using ISO 9613-2, an international standard for attenuation of sound during propagation outdoors. Given sound source inputs and locations over an input Digital Elevation Map, GIS compatible file types of spatially explicit sound pressure level predictions can be produced by this model. This tool allows for ecologists and park managers to get a better understanding of how anthropogenic noise is affecting soundscapes in natural environments. [Work supported by United Technologies Corporation Professorship.]

Statistical validation of an LTE emulation tool using live video streaming over reliable transport protocols

Multimedia services such as Live Video-Streaming (LVS) or Video on Demand are the main drivers behind the notable traffic growth in cellular networks. This fact has attracted the interest of both academia and telcos in improving the end user’s quality of experience. For this reason, the development of test benches for conducting traffic studies in this type of telecommunication system is necessary and emulators are a good option to validate possible solutions without affecting the real systems. However, most works addressing the emulation of Long-Term Evolution (LTE) systems do not validate their outcomes with real environments and hence ignore critical parameters such as the impact of wireless propagation under different scenarios. Therefore, the goal of this paper is to validate an outdoor propagation model for LVS so that accurate studies of traffic characterization in LTE networks can be carried out using an emulation tool. The validation is done through a statistical analysis of variance (ANOVA) of Quality of Service metrics, comparing the results obtained in an LTE-emulated scenario with those obtained in a real LTE test bench. For this study, the LVS service runs on top of a reliable transport protocol. Specifically, we test the Real-Time Message Protocol and the MPEG Dynamic Adaptive Streaming over HTTP (DASH) protocol, both using TCP at the transport layer. According to the results, the propagation model that better matches the real environment under the considered conditions is the Nakagami-m propagation model with m = 5.

Cluster Characterization of 3-D MIMO Propagation Channel in an Urban Macrocellular Environment

Multidimensional characterization of outdoor urban macrocellular propagation channels is essential for the analysis and design of next-generation (5G and beyond) cellular massive MIMO (multiple-input-multiple-output) systems. Since most massive MIMO arrays will extend in two or three dimensions, an understanding of 3-D parameters (i.e., azimuth and elevation) of the multipath components (MPCs) is required. This paper presents an extensive measurement campaign for 3-D outdoor propagation channels in an urban macrocellular environment. Measurements were performed with a 20 MHz wideband polarimetric MIMO channel sounder centered at 2.53 GHz and MPCs were extracted using RIMAX—an iterative maximum likelihood algorithm. The physical propagation mechanisms of the observed discrete MPCs are explained in terms of waveguiding, over-the-rooftop propagation, and scattering by far-away objects. MPCs exhibit clustering in the temporal and spatial domains; both intra- and inter- cluster parameters and their relevant statistics are provided. We also extract diffuse MPCs, show that they can comprise a moderate portion of the overall energy, and provide a statistical characterization.

Outdoor Path Loss Predictions Based on Extreme Learning Machine

In a typical outdoor environment, the propagation of radio waves is usually random in nature, to the extent that the characterization of the wireless channel often becomes very difficult. Several models have been developed to predict the average Received Signal Strength (RSS) for specified distance ranges. However, the use of deterministic models requires high computational efficiency while the prediction results of empirical models may not be as accurate as required. On machine learning approach, the performances of multi-layered feed-forward network models are limited by slow convergence and local minimum, such that a global optimal solution is not guaranteed. In this paper, Extreme Learning Machine (ELM) algorithm is considered in the development of an optimal path loss prediction model for outdoor propagation scenario. Single Hidden Layer Feed-forward Neural Networks (SHLFNNs) are trained and tested with the path loss data that were computed based on the RSS data of a commercial 1800 MHz base station located along Lagos-Badagry highway in Nigeria. The training speed, learning effectiveness, and the generalization ability of Artificial Neural Network Back-Propagation (ANN-BP) and ELM algorithms are analysed. Experimental results show that ELM models are 140 times faster to train than the ANN-BP models. On prediction accuracy, the outputs of ELM, ANN-BP, Okumura–Hata, and COST-231 models have Root Mean Squared Error (RMSE) values of 2.896, 2.449, 7.456, and 6.116 dB respectively; and regression coefficient (R) values of 0.959, 0.973, 0.935, and 0.935 respectively, when compared to the target variable of the training dataset. When the models were tested with new input data that were excluded from the training process, RMSE values of 4.250, 6.622, 8.732, and 7.087 respectively; and R values of 0.893, 0.876, 0.904, and 0.904 respectively are obtained. In conclusion, the findings of this study confirm that ELM algorithm guarantees an optimal path loss model with fast training convergence, high prediction accuracy, and good generalization ability for radio network planning and optimization in outdoor environments.