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This article provides a review of the Citizen Broadband Radio Service (CBRS) and its characteristics. It also describes the Spectrum Access System, which allows the bands not used by primary users to be intelligently occupied by secondary users to optimize this resource. As a rule, CBRS operates between 3550 MHz and 3700 MHz to allow users’ connectivity from different operators in high-traffic locations. Using Neutral Hosts minimizes the installation and operation costs of the Advanced Mobile Service’s operators. CBRS also functions as a private LTE network with several advantages over other wireless network technologies. This innovative proposal marks a milestone in shifting from fixed allocation of the radio spectrum to dynamic controlled access, enabling connectivity to a wide range of wireless devices.

Indoor tracking and navigation (ITN) mainly depend on indoor localization. An impulse radio ultra-wideband (IR-UWB) is the most advanced technology for precision indoor localization. Besides its precision, the IR-UWB also has low complex hardware, low power consumption, and a flexible data rate that makes it the ideal candidate for ITN. However, two significant challenges impede the achievement of high-resolution accuracy and optimum performance: non-line-of-sight (NLOS) channel condition and multipath propagation (MPP). To enhance the performance under these conditions, the ranging error is estimated and corrected using parameters' uncertainties. The uncertainties in the channel's parameters have a relationship with the error, and these uncertainties are induced due to the NLOS and MPP propagation conditions. The parameters are collected in real-time experimental setups in two different environments. A proposed fuzzy inference model utilizes these uncertainties and the relationship to estimate ranging errors. The model is evaluated, and its performance is gauged in terms of residual ranging error cumulative distribution, root mean square error, and outage probability parameters using experimental measurements and compared with the state-of-the-art work. Moreover, the proposed fuzzy model is evaluated for computational complexity in terms of execution time and compared with the state-of-the-art work. The time is estimated on the targeted embedded system. The experimental and simulated results show that the proposed model effectively minimizes the ranging errors and computational burden. Moreover, the model does not induce a delay in estimating ranging error due to the non-statistical based solution.

Cognitive radio (CR)-based Internet of Things (IoT) system is an effective step toward a world of smart technology. Many frameworks have been proposed to build CR-based IoT systems. The CR-based IoT frameworks are the key points on which this survey focuses. Efficient spectrum sensing and sharing are the main functional components of the CR-based IoT. Reviews of recent SS and sharing approaches are presented in this survey. This survey classifies the SS and sharing approaches and discusses the merits and limitations of those approaches. Moreover, this survey discusses the design factors of the CR-based IoT and the criteria by which the proper SS and access approaches are selected. Furthermore, the survey explores the integration of newly emerging technologies with the CR-based IoT systems. Finally, the survey highlights some emerging challenges and concludes with suggesting future research directions and open issues.

For years, emergency attendance institutions in Ecuador worked separately and not all of them had a 24/7 service, resulting in duplicated efforts, a waste of the scarce resources, and an absence of generalized technology. In 2012, Ecuador created an Integrated Security Service, called ECU 911, to address the need of an emergency service articulating all the first response institutions. The ECU 911 relies on the Enhanced 911 technology, having a countrywide presence. Since then, Ecuador has implemented 16 public-safety answering points and 11 decentralized operative rooms, covering all Ecuadorian territory and serving to a population of about 17 million people. The overview presented in this paper demonstrates how the advanced technology supports this new model of emergency attention service based on an Enhanced 911 platform. In addition, the achievements and challenges required to become a Next-Generation 911 service are discussed.

In multi-hop underwater acoustic sensor networks (UWASNs), packet collisions due to hidden and local nodes adversely affect throughput, energy efficiency and end-to-end delay. Existing medium access control (MAC) protocols try to solve the problem by utilizing a single-phase contention resolution mechanism, which causes a large number of control packet exchanges and energy overhead. In this paper, we introduce a MAC protocol that splits this single-phase contention resolution mechanism into two phases to provide efficient multi-hop networking. In the first phase, local nodes are eliminated from the contention, and in the later phase, the adverse effects of hidden nodes are mitigated. This two-phased contention resolution provides higher energy efficiency, better throughput and shorter end-to-end delay, and it also enables adaptability for different network architectures. A probabilistic model of the proposed protocol is also developed to analyse the performance. The proposed protocol has been evaluated through quantitative analysis and simulation. Results obtained through quantitative analysis and simulation reveal that the proposed protocol achieves significantly better energy efficiency, higher and more stable throughput and lower end-to-end delay compared to existing protocols, namely T-Lohi and slotted floor acquisition multiple access (S-FAMA).

Television White Spaces (TVWS)-based cognitive radio systems can improve spectrum efficiency by facilitating opportunistic usage of television broadcasting spectrum by secondary users without interfering with primary users. Previously applied models introduce missed detection errors, giving a limited estimation of the spectrum occupancy, which does not correspond to the reality of its usage, hence resulting in a partial waste of this resource. Considering jointly parameters like false alarm probability and detection probability, this article proposes a probabilistic model that can identify TVWS with improved accuracy. The proposed model considers energy detection criteria, combined with simultaneous sensing of the noise and of the signal from primary users. In order to demonstrate the model effectiveness, a low-cost Mobile Spectrum Sensing Station prototype was designed, implemented, and subsequently mounted on a vehicle. More than eight million spatio-temporally variant data samples were collected by scanning the UHF-TV spectrum of 500−698 MHz in the city of Windsor, ON, Canada. Analysis of the collected data showed that the proposed model achieves an accuracy improvement of about 9.6% compared to existing models, demonstrating that TVWS vary with spatial displacement and increasing significantly in the rural areas. Even in the most crowded spectrum zone, about 28% of the channels are identified as TVWS, and this number increases to a maximum of 60% in less crowded regions in urban areas. We conclude that the proposed model improves the TVWS detection compared with other used models, and also that the elements considered in this research contribute to reduce the complexity of the mathematical calculations while maintaining the accuracy. A low-cost open-source sensing station has been designed and tested, which represents an operative and useful data source in this setting.

A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.