This article presents the analysis, design, simulation, construction and characterization of an axial radiation helical antenna with medium gain (11dBi) and circular polarization as a proposed use for the emergency water information network. Due to its application in the earth station, there are no dimensional limits. The parameters and results for an operating frequency of 915 MHz are presented.

Binary Polar Codes (BPCs) have advantages of high-efficiency and capacity-achieving but suffer from large latency due to the Successive-Cancellation List (SCL) decoding. Non-Binary Polar Codes (NBPCs) have been investigated to obtain the performance gains and reduce latency under the implementation of parallel architectures for multi-bit decoding. However, most of the existing works only focus on the Reed-Solomon matrix-based NBPCs and the probability domain-based non-binary polar decoding, which lack flexible structure and have a large computation amount in the decoding process, while little attention has been paid to general non-binary kernel-based NBPCs and Log-Likelihood Ratio (LLR) based decoding methods. In this paper, we consider a scheme of NBPCs with a general structure over GF(2m). Specifically, we pursue a detailed Monte-Carlo simulation implementation to determine the construction for proposed NBPCs. For non-binary polar decoding, an SCL decoding based on LLRs is proposed for NBPCs, which can be implemented with non-binary kernels of arbitrary size. Moreover, we propose a Perfect Polarization-Based SCL (PPB-SCL) algorithm based on LLRs to reduce decoding complexity by deriving a new update function of path metric for NBPCs and eliminating the path splitting process at perfect polarized (i.e., highly reliable) positions. Simulation results show that the bit error rate of the proposed NBPCs significantly outperforms that of BPCs. In addition, the proposed PPB-SCL decoding obtains about a 40% complexity reduction of SCL decoding for NBPCs.

In dense radio frequency identification (RFID) situations where the coverage of multiple interrogators overlaps, a key challenge is to mitigate interrogator-involved collisions. Among the solutions that have been proposed to reduce or avoid such collisions, Geometric Distribution Reader Anti-collision (GDRA) protocol achieves the highest throughput exploiting Geometric distribution to minimise contention among interrogators. This approach is compatible with current RFID protocols, such as EPC Gen2, ISO18000-6C and ETSI EN 302 208–1 without extra hardware support. In this paper, based on GDRA, we propose an enhanced protocol, called Dynamic GDRA (DGDRA), in which different interrogators dynamically and independently adapt their own Geometric distributions based on the experienced number of successful transmissions and collisions. Simulation results confirm that the proposed DGDRA provides higher throughput and enhances fairness performance compared to the original anti-collision scheme.

Internet of Things (IoT) radio networks are becoming popular in several scenarios for short-range applications (e.g., wearables and home security) and medium-range applications (e.g., shipping container tracking and autonomous farming). They have also been proposed for water monitoring in flood warning systems. IoT communications may use long range (LoRa) radios working in the 915 MHz industrial, scientific and medical (ISM) band. In this research, we study the propagation characteristics of LoRa chirp radio signals close to and over water in a tropical meadow region. We use as a case study the Colima River in Mexico. We develop a novel point-to-point IoT measurement sounding system that does not require decoding of LoRa propriety bursts and provides accurate power versus distance profiles along the riparian zone of a steeply dropping mountain river. We used this system to obtain the measurements reported in this work, which are also analyzed and modeled. The results show that the LoRa signal propagation over water exhibits a log-normal distribution. As a result of the chirp signal processing, two new experimental path loss models are presented. The path loss results show a considerable degradation of the received signal power over water within vegetation and less signal degradation at antenna heights closer to the water surface.

In this paper, a method for the study XBee latency is researched. Study of an XBee radio link is important when considering machine control over wireless. Furthermore, knowledge of an XBee latency probability distribution is useful in the simulation of machine control over wireless. In this research, a camera gimble, typical of those used by expert observers with drones was proposed as the machine control activity. The test bed used was created using two XBee IEEE 802.15.4 MaxStream modules in a point to point configuration. In drone mounted machine control over an XBee channel a controller sends command messages to a flying drone. Lower latency in camera control yields shorter reaction times for camera operators and a more comfortable operation experience for untrained expert observers.

Urban flooding is one of the major issues in many parts of the world, and its management is often challenging. One of the challenges highlighted by the hydrology and related communities is the need for more open data and monitoring of floods in space and time. In this paper, we present the development phases and experiments of an Internet of Things (IoT)-based wireless sensor network for hydrometeorological data collection and flood monitoring for the urban area of Colima-Villa de Álvarez in Mexico. The network is designed to collect fluvial water level, soil moisture and weather parameters that are transferred to the server and to a web application in real-time using IoT Message Queuing Telemetry Transport protocol over 3G and Wi-Fi networks. The network is tested during three different events of tropical storms that occurred over the area of Colima during the 2019 tropical cyclones season. The results show the ability of the smart water network to collect real-time hydrometeorological information during extreme events associated with tropical storms. The technology used for data transmission and acquisition made it possible to collect information at critical times for the city. Additionally, the data collected provided essential information for implementing and calibrating hydrological models and hydraulic models to generate flood inundation maps and identify critical infrastructure.

In this paper, a new method for augmenting current self-localization methods for autonomous based on Global Navigation Systems (GNSS) and Lidar is introduced as a backup system for primary equipment. The method uses Radio Frequency Identity Tags (RFID) running under a modified EPC Gen2 Standard. Simulated results are presented for a representative 6. 54km circular track around Loughborough, UK town centre with a 911 items inventory of roadside furniture. The virtual test track as input for an RFID tag simulator that uses an interrogator/inventory protocol. The technique is shown to be a good candidate for improving safety in Autonomous Vehicles and position finding for vehicles in general.

In Long Term Evolution (LTE) Resource Allocation Algorithms (RAAs) are an area of work where researchers are seeking to optimize the efficient use of scarce radio resources. The selection of an optimal Modulation and Coding Scheme (MCS) that allows LTE to adapt to channel conditions is a second area of ongoing work. In the wireless part of LTE, these two factors, RAA and MCS selection, are the most critical in optimization. In this paper, the performance of three resource allocation schemes is compared, and a new allocation scheme, Average MCS (AMCS) allocation, is proposed. AMCS is seen to outperform both “Minimum MCS (MMCS)” and “Average Signal to Interference and Noise Ratio MCS (SINR AMCS)” in terms of improvements to LTE Uplink (UL) performance. The three algorithms were implemented in the Vienna LTE-A Uplink Simulator v1.5.

Urban flooding is one of the major issues in many parts of the world and its management often challenging. Here we present Internet of Things (IoT) approach for monitoring urban flooding in the City of Colima, Mexico. A network of water level and weather sensors have been developed along with a web-based data platform integrated with IoT techniques to retrieve data using 3G/4G and Wi-Fi networks. The developed architecture uses the Message Queuing Telemetry Transport protocol to send real-time data packages from fixed nodes to a server that stores retrieved data in a non-relational database. Data can be accessed and displayed through different queries and graphical representations, allowing future use in flood analysis and prediction. Additionally, machine learning algorithms are integrated into the system for short-range water level predictions at different nodes of the network.

This paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.

In this paper, a novel two dimension (2-D) direction of arrival (DOA) estimation method based on complementary sequence and ESPRIT algorithm under parallel coprime Arrays is proposed for multiple input and multiple output (MIMO) system. Unlike the traditional method, the complementary sequence is used as the transmitted far-field signals. Due to the orthogonality of the complementary sequence, the DOA estimation performance can be improved. Based on the parallel coprime array, the novel ESPRIT algorithm can be used to acquire accurate DOA estimation by searching the coincide values from ambiguous estimation results. In addition, we give the experimental results and show that the proposed algorithms can obtain higher DOA estimation resolution and distinguish more targets.

Wireless sensor networks are a current area of interest for many researchers, however surprisingly few have actually been deployed. In this paper we present preliminary results from a series of experiments designed to assess the viability of using existing mobile phone networks in developing countries to create flood warning systems. Creation of a flood warning network involves placing wirelessly connected nodes on all significant tributaries of a river system often over several hundreds of square kilometres. Rain is one of the principal causes of signal change in mobile networks. To assess the effect of the above on associated Internet of Things (IoT) flood alert systems, measurements were conducted in the UK and Mexico to determine the attenuation of line of sight (LOS) and ground multipath propagation due to either rain or excess surface water. Both components are analysed using ray tracing simulation software in addition to the real-time field measurements with the mobile hand set 'app' G-NetTrack Pro. Measurement experience gleaned from the UK campaign has been used to formulate a more comprehensive hand set based strategy in the Colima flood zone in Mexico, the results of which are also summarized in this paper. It is believed that both the above measurement and ray trace modelling exercises may be used to further optimize protocols required to address the propagation needs of future 4G/5G networks.

This paper presents the results of a wideband channel measurement campaign carried out in an indoor environment with representative inventory of a factory. The measurements were carried out using a frequency domain channel sounder from 3.4 - 3.8 GHz and the virtual array method was adopted for averaging small-scale fading effects. From the average power delay profile (APDP), parameters for the Saleh-Valenzuela (S-V) model were extracted for line-of-sight (LoS) and non line-of-sight (NLoS) sites. The ray decay from the S-V model increased with cluster delay for all LoS sites and the delay spread for NLoS sites were higher than LoS locations. The NLoS delay spread was also higher than the results obtained at 2.4 GHz for the same measurement locations. The APDPs from both LoS and NLoS sites showed clustering effects with a mean cluster number of 8/7 for LoS/NLoS sites.

Resilience is an indicator of the ability of systems to withstand disruption within acceptable degradation parameters and also their recovery time. It is essential for public policies to understand how the population reacts to a particular risk. In this paper we have performed a study that quantitatively measures perceptions of flooding and resilience to flooding in the city of Colima-Villa de Alvarez, Mexico 2018-2019. A resilience index has been applied to ten zones of the city. In our research we assessed risk perception through a city-wide survey with questions based on a Likert scale. An analysis was performed on public knowledge of the existing security protocols for floods and evaluated the public perception of the availability of critical services, such as fresh water, electricity, food, drainage, communications and public transport during a flash flood events. This research has identified populated low resilience zones that can be considered as priorities for resource and effort to mitigate floods and their impacts. The novel resilience index developed in this work can also be applied to other type of risk that humans face and used as a basis for discussions about urban resilience.

Flooding is one of the most frequent and costly natural disasters affecting mankind. However, implementing Internet of Things (IoT) technology to monitor river behavior may help mitigate or prevent future disasters. This article outlines the hardware development of an IoT system (RiverCore) and defines an application scenario in a specific hydrological region of the state of Colima (Mexico), highlighting the characteristics of data acquisition and data processing used. Both fixed position and moving drifter node systems are described along with web-based data acquisition platform developments integrated with IoT techniques to retrieve data through 3G cellular networks. The developed architecture uses the Message Queuing Telemetry Transport (MQTT) protocol, along with encryption and security mechanisms, to send real-time data packages from fixed nodes to a server that stores retrieved data in a non-relational database. From this, data can be accessed and displayed through different customizable queries and graphical representations, allowing future use in flood analysis and prediction systems. All of these features are presented along with graphical evidence of the deployment of the different devices and of several cellular communication and on-site data acquisition tests.

This paper presents a new way to estimate delay spread in machine workspaces by using fractal geometry. In this way, inventories can be created quickly and used within a ray tracing software to estimate the radio environment of machine workspaces as part of the planning process. Delay spread is an important metric in assessing the performance of wireless technologies. Predicted 5G cyber-physical systems in workplaces will require high-density use of wirelessly connected machine-to-machine RF modules. In workshops, the surfaces and edges of machines, shelves, and furniture influence the multipath/power delay profile of the space. However, with the fast construction pace and high occupancy of buildings, it is impractical to characterize the location as building work progresses. Consequently, it becomes more probable that the radio communication system deployed will perform suboptimally. In this work, the Wi-Fi band was investigated. In addition, representative simulations were also carried out at millimetre wave frequencies of 28 GHz and 60 GHz. (C) 2019 Elsevier B.V. All rights reserved.

A compact, circular UWB fractal antenna with triple reconfigurable notch rejection bands is proposed. It rejects the crowded frequency bands WiMAX, WLAN and X band interferences produced in UWB communication systems. The proposed fractal structure consists of a basic circular patch with circular fractal iterations. By employing this new structure of fractals, the overall size of antenna is reduced 53% to 21 x 25 mm, in comparison with traditional circular monopole antenna. The implemented antenna operates at 3.1-10 GHz. Re-configurability is realized by designing slots and split ring resonators in desired frequencies with the attached PIN diodes. WLAN band rejection was realized by creating a pair of optimized L-shaped slots in the ground plane. By etching a split ring resonator and a U-shaped slot, X and WiMAX bands were also rejected. Furthermore, by attaching diodes to aforementioned slots and designating the diodes on/off, different bands can be included or rejected. In time domain, the antenna properties are evaluated by a figure of merit called fidelity factor. Finally, the antenna properties are measured in anechoic chamber and the results agrees with simulation findings. (C) 2019 Elsevier GmbH. All rights reserved.

In this paper different characteristics of patch antenna with two different Substrates’ materials have been analyzed. The initial antenna has been fabricated and tested. Rectangular slots have been etched in the radiating patch and ground. Two parasitic patches have been loaded to the antenna. Two different materials have been used in the substrate of the antenna and their impedance bandwidth and efficiency have been compared to each other. The Transmission Feed line is used to feed the antenna under consideration. The overall size of the final proposed antenna on Preperm L-450 is 10×20𝑚𝑚2. The impedance bandwidth of the proposed antenna is 5.44GHz and a return loss of 62.38 dB has been obtained at the center frequency of 16.93GHz. This antenna on the basis of its features can be used for Ku- Band communication.

A prototyping method for dielectrically loaded antennas is presented. Dielectric loading has been used with horn antennas, feeds, and lenses. Dielectrics have also been used for coating antennas submerged in water and biological matter and have led to improvements in bandwidth and efficiency as well as antenna miniaturisation. The authors present a new technique to produce variable dielectrics with permittivity from 6 to 28 using two commonly available powders, titanium dioxide (used in foods) and magnesium silicate (used in talcum powder). An example spherical helical ball antenna is used to demonstrate the process. In this antenna, the mixed powders were encased in a 3D printed shell that achieved a reduction in diameter of the spherical antenna by a factor of 1.85. The technique aids rapid prototyping and optimisation using search algorithms.

This paper investigates signal detection algorithms for multiple input/multi output (MIMO) systems; an essential technology to be implemented in fifth generation wireless communications (5G). The performances of coherent and non-coherent detection techniques in a single input multiple output (SIMO) and a MIMO system are compared in a Rayleigh fading channel with M-PSK signal input. The receiver diversity technique using maximum ratio combining (MRC) was examined, together with Alamouti space time block codes (STBC). The evaluation of both schemes characterizes their respective drawbacks and also provides a premise in the selection; for optimum performance with regards to 5G MIMO systems. The simulated parameters for benchmarking the detection schemes investigated were bit error rate (BER), ergodic capacity and outage probability.