Wireless Body Area Nanonetworks via Vascular Molecular Communication.

Advancements in biotechnology and molecular communication have enabled the utilization of nanomachines in Wireless Body Area Networks (WBAN2) for applications such as drug delivery, cancer detection, and emergency rescue services. To study these networks effectively, it is essential to develop an ideal propagation model that includes the channel response between each pair of in-range nanomachines and accounts for the interference received at each receiver node. In this paper, we employ an advection-diffusion equation to obtain a deterministic channel matrix through a vascular WBAN2. Additionally, the closed forms of inter-symbol interference (ISI) and co-channel interference (CCI) are derived for both full duplex (FDX) and half duplex transmission (HDX) modes. By applying these deterministic formulations, we then present the stochastic equivalents of the ideal channel model and interference to provide an innovative communication model by simultaneously incorporating CCI, ISI, and background noise. Finally, we evaluate the results with numerous experiments and use signal-to-interference-plus-noise ratio (SINR) and capacity as metrics.

Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach.

The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time processing at edge servers, existing message queue systems face challenges in adapting to changing system conditions, such as fluctuations in the number of devices, message size, and frequency. This necessitates the development of an approach that can effectively decouple message processing and handle workload variations in the AIoT computing environment. This study presents a distributed message system for AIoT edge computing, specifically designed to address the challenges associated with message ordering in such environments. The system incorporates a novel partition selection algorithm (PSA) to ensure message order, balance the load among broker clusters, and enhance the availability of subscribable messages from AIoT edge devices. Furthermore, this study proposes the distributed message system configuration optimization algorithm (DMSCO), based on DDPG, to optimize the performance of the distributed message system. Experimental evaluations demonstrate that, compared to the genetic algorithm and random searching, the DMSCO algorithm can provide a significant improvement in system throughput to meet the specific demands of high-concurrency AIoT edge computing applications.

Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks.

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients' health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

Cooperative Multiband Spectrum Sensing Using Radio Environment Maps and Neural Networks.

Cogitive radio networks (CRNs) require high capacity and accuracy to detect the presence of licensed or primary users (PUs) in the sensed spectrum. In addition, they must correctly locate the spectral opportunities (holes) in order to be available to nonlicensed or secondary users (SUs). In this research, a centralized network of cognitive radios for monitoring a multiband spectrum in real time is proposed and implemented in a real wireless communication environment through generic communication devices such as software-defined radios (SDRs). Locally, each SU uses a monitoring technique based on sample entropy to determine spectrum occupancy. The determined features (power, bandwidth, and central frequency) of detected PUs are uploaded to a database. The uploaded data are then processed by a central entity. The objective of this work was to determine the number of PUs, their carrier frequency, bandwidth, and the spectral gaps in the sensed spectrum in a specific area through the construction of radioelectric environment maps (REMs). To this end, we compared the results of classical digital signal processing methods and neural networks performed by the central entity. Results show that both proposed cognitive networks (one working with a central entity using typical signal processing and one performing with neural networks) accurately locate PUs and give information to SUs to transmit, avoiding the hidden terminal problem. However, the best-performing cognitive radio network was the one working with neural networks to accurately detect PUs on both carrier frequency and bandwidth.

A long distance telesurgical demonstration on robotic surgery phantoms over 5G.

PURPOSE: Using robotic technology and communications infrastructure to remotely perform surgery has been a persistent goal in medical research in the past three decades. The recent deployment of the Fifth-Generation Wireless Networks has revitalized the research efforts in the telesurgery paradigm. Offering low latency and high bandwidth communication, they are well suited for applications that require real-time data transmission and can allow smoother communication between surgeon and patient, making it possible to remotely perform complex surgeries. In this paper, we investigate the effects of the 5 G network on surgical performance during a telesurgical demonstration where the surgeon and the robot are separated by nearly 300 km. METHODS: The surgeon performed surgical exercises on a robotic surgery training phantom using a novel telesurgical platform. The master controllers were connected to the local site on a 5 G network, teleoperating the robot remotely in a hospital. A video feed of the remote site was also streamed. The surgeon performed various tasks on the phantom such as cutting, dissection, pick-and-place and ring tower transfer. To assess the usefulness, usability and image quality of the system, the surgeon was subsequently interviewed using three structured questionnaires. RESULTS: All tasks were completed successfully. The low latency and high bandwidth of the network resulted into a latency of 18 ms for the motion commands while the video delay was about 350 ms. This enabled the surgeon to operate smoothly with a high-definition video from about 300 km away. The surgeon viewed the system's usability in a neutral to positive way while the video image was rated as of good quality. CONCLUSION: 5 G networks provide significant advancement in the field of telecommunications, offering faster speeds and lower latency than previous generations of wireless technology. They can serve as an enabling technology for telesurgery and further advance its application and adoption.

Evaluation on the information about absolute and relative indications of cesarean sections available on popular websites / Avaliação das informações sobre indicações absolutas e relativas de cesarianas disponíveis em sites populares

Abstract Objectives: to evaluate the reliability of information available on popular websites, in other words, websites aimed lay pregnant women, about absolute and relative indications for cesarean sections. Methods: this was a descriptive/comparative study based on the popular websites most likely to be visited by lay pregnant women and that contained information about indications for absolute and relative cesarean sections. Cohen's Kappa index of agreement was used to analyze the reliability degree on the indications for cesarean sections presented on the websites and the scientific evidence. Results: there was a higher prevalence (62.63%) of information on the indications for cesarean sections that did not mention whether the indication was absolute or relative, and of these indications, 40.74% were not indications for cesarean sections. Low agreement was also observed among websites and the scientific evidence when the website mentioned the indication for cesarean section was absolute or relative. Conclusion: this study showed that the reliability of the information on absolute and relative indications for cesarean sections available in popular websites is questionable.

Resumo Objetivos: avaliar a confiabilidade das informações disponíveis em sites populares, ou seja, sites voltados para gestantes leigas, sobre indicações absolutas e relativas de cesarianas. Métodos: estudo descritivo/comparativo, baseado nos sites populares mais prováveis de serem visitados por gestantes leigas e que traziam informações sobre as indicações de cesarianas absolutas e relativas. Para analisar o grau de confiabilidade das indicações de cesarianas apresentadas pelos sites e a evidência cientifica, foi realizado o índice de concordância de Kappa de Cohen. Resultados: houve maior prevalência (62,63%) de informações de indicações de cesarianas que não mencionavam se a indicação apresentada era absoluta ou relativa, sendo que destas, 40,74% não eram indicações de cesarianas. Observou-se, concordância baixa entre os sites e a evidência cientifica quando o site mencionava que a indicação de cesariana era absoluta ou relativa. Conclusão: este estudo demonstrou que a confiabilidade das informações acerca das indicações absolutas e relativas de cesarianas disponíveis em sites populares é questionável

Uso de las plataformas tecnológicas para generar campañas exitosas de comunicación en salud / Use of technological platforms to generate successful health communication campaigns

Fundamento: el papel de las plataformas tecnológicas es radical en cualquier propuesta de comunicación en salud, máxime si va dirigida a estudiantes universitarios con el fin de generar campañas exitosas en la población. Objetivo: identificar los componentes teórico-metodológicos y prácticos que sustentan el uso de las nuevas tecnologías, desde su enfoque social, junto con los aportes específicos de las plataformas virtuales, para la implementación de una propuesta de comunicación en salud. Métodos: se realizó una investigación con enfoque cualitativo, en la Universidad Católica de Cuenca, carrera de Medicina durante septiembre 2021-marzo 2022. Se emplearon métodos teóricos y empíricos: entrevistas en profundidad, revisión documental y grupos focales. Resultados: se evidenció falta de conocimientos por los estudiantes de la carrera de Medicina sobre los modelos de comunicación y su implementación con el uso de nuevas tecnologías referentes a campañas preventivas de salud. Se identificaron los componentes teórico-metodológicos y prácticos que sustentan el uso de las nuevas tecnologías, junto con los aportes específicos de las plataformas virtuales para la implementación de una propuesta de comunicación en salud sobre promoción de estilos de vida saludables y prevención de enfermedades, la cual fue valorada por criterios de expertos. Conclusiones: el producto diseñado resultó adecuado: proporcionó que los docentes, estudiantes médicos, futuros profesionales y funcionarios de la salud estén mejor preparados para comunicar, de forma efectiva, campañas de prevención y cuidado en salud, en disímiles contextos más allá del entorno nacional.

Background: the role of technological platforms is radical in any health communication proposal, especially if it is aimed at university students in order to generate successful campaigns in the population. Objective: to identify the theoretical-methodological and practical components that support the use of new technologies, from their social approach, together with the specific contributions of virtual platforms, for the implementation of a health communication proposal. Methods: an investigation with a qualitative approach was carried out at the Catholic University of Cuenca, Medicine degree from September 2021 to March 2022. Theoretical and empirical methods were used: in-depth interviews, documentary review and focal groups. Results: lack of knowledge was evidenced by the students of the Medicine degree about communication models and their implementation with the use of new technologies related to preventive health campaigns. The theoretical-methodological and practical components that support the use of new technologies were identified, together with the specific contributions of virtual platforms for the implementation of a health communication proposal on the promotion of healthy lifestyles and disease prevention, which was valued by expert criteria. Conclusions: the designed product was adequate: it provided that teachers, medical students, future professionals and health managers get prepared to effectively communicate prevention and health care campaigns in dissimilar contexts beyond the national environment.

Tecnologías 2.0 para la innovación y el desarrollo comunicacional en salud / Technologies 2.0 for innovation and communication development in health

Fundamento: las tecnologías 2.0 y las redes sociales son herramientas de comunicación que permiten a los usuarios compartir noticias; por lo que han tomado gran importancia para las autoridades sanitarias en Ecuador en temas de salud. Objetivo: indagar sobre el plan de comunicación digital que divulgó el Ministerio de Salud Pública, a través de su cuenta en Facebook, para mantener a los ciudadanos informados sobre las medidas de bioseguridad contra la COVID-19 y su contribución a la educación en salud. Métodos: se realizó una investigación con enfoque cualitativo en la página oficial de Facebook del Ministerio de Salud Pública del Ecuador durante los meses enero-julio de 2021. Se utilizaron métodos teóricos para la fundamentación de la investigación y empíricos: la observación y la entrevista a profesionales relacionados con el rubro de la comunicación digital. Resultados: la campaña #JuntosPorLaSalud fue desarrollada bajo un estilo de tipo informativo y de tono formal para la creación de contenidos con imágenes; además como protocolo de seguridad de la información se colocó la palabra FALSO, una marca de agua para mostrar el fraude y el mal uso interpretativo de los post en tiempos de pandemia; de esta manera mantuvo un margen institucional respetable y de credibilidad frente a los usuarios. Conclusiones: el plan comunicacional digital divulgado en Facebook sirvió como un canalizador y altavoz de los mensajes emitidos por la institución; en todo momento se logró mantener a los usuarios informados sobre temas de prevención, bioseguridad y vacunas contra la COVID-19.

Background: 2.0 technologies and social networks are communication tools that allow users to share news; therefore, they have taken on great importance on health issues for the health authorities in Ecuador. Objective: to inquire about the digital communication plan published by the Ministry of Public Health, through its Facebook account, to keep citizens informed about biosecurity measures against COVID-19 and its contribution to health education. Methods: an investigation with a qualitative approach was carried out on the official Facebook page of the Ministry of Public Health of Ecuador from January to July 2021. Theoretical methods were used to support the investigation and empirical ones: observation and interview with professionals related to the field of digital communication. Results: the #JuntosPorLaSalud campaign was developed under an informative style and a formal tone for the creation of content with images; in addition, as an information security protocol, the word FALSE was placed, a watermark to show fraud and misuse of posts in times of pandemic; In this way, it maintained a respectable institutional margin and credibility with respect to users. Conclusions: the digital communication plan disclosed on Facebook served as a channel and loudspeaker for the messages issued by the institution; at all times it was possible to keep users informed on issues of prevention, biosecurity and vaccines against COVID-19.

SIPEA: Aplicación web para el Hospital Celia Sánchez Manduley en Manzanillo / SIPEA: Web Application for Celia Sánchez Manduley Hospital in Manzanillo

Anemia is the most common blood disorder in the world, affecting millions of people yearly. It has multiple causes and jeopardizes development, growth and learning. Current tools provide non-hematologist doctors with just numbers. The present paper proposes a web application intended to provide doctors at Celia Sánchez Manduley Hospital in Manzanillo with a tool for determining the morphologic type of anemia, creating a list of possible causes, and also storing patient data in a database for future researches. As an information system, the website constitutes a powerful tool for the decision-making process, in particular, the diagnostic process, intended to provide more detailed information on anemia as well as to foster the information management at the hospital. For the application, HTML, CSS, JavaScript and PHP were used as languages; Apache as a web server; CodeIgniter as a PHP framework; MariaDB as a database management system; and Visual Studio Code as a development environment(AU)

La anemia afecta a millones de personas anualmente, esta obedece a múltiples causas y compromete el crecimiento, desarrollo y aprendizaje. Las herramientas actuales ofrecen al médico no especialista en hematología solo cifras. El presente trabajo propone una aplicación web con la cual se pretende brindar a los médicos del Hospital Celia Sánchez Manduley en Manzanillo una herramienta para la determinación del tipo morfológico de anemia, la elaboración de un listado de las posibles causas que la originan, así como el almacenamiento de datos de los pacientes para futuras investigaciones, y con ello contribuir a la toma de decisiones, en particular, al proceso de diagnóstico, y a una mejor gestión de información en el hospital. Para la aplicación se utilizaron los lenguajes HTML, CSS, JavaScript y PHP, el servidor web Apache, el framework PHP CodeIgniter, el gestor de base de datos MariaDB y el entorno de desarrollo Visual Studio Code(AU)

Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing.

Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots.

Traffic-driven ions motion optimization-based clustering routing protocol for cognitive radio sensor networks.

In cognitive radio sensor networks, single clustering protocol cannot simultaneously satisfy the various requirements of time-triggered and event-driven traffic, as a result, different kinds of clustering protocols are designed to serve them separately. In addition, for event-driven traffic, the long delay incurred by clustering and searching for available routes after events results in poor timeliness of information transmission. In order to solve above problems, a traffic-driven ions motion optimization-based clustering routing protocol (TD-IMOCRP) is proposed in this paper. For the first time, time-triggered and event-driven traffic can be served by a single clustering protocol. To be specific, ions motion optimization algorithm is leveraged to automatically determine the optimal number of clusters and form basic clustering structure. In this case, time-triggered traffic can be periodically served. Priority-based schedule and corresponding frame structure are designed to ensure priority delivery of event-driven information. The clustering architecture built for time-triggered traffic is leveraged, and there is no cluster construction and route selection after emergent events. Only the CRSNs nodes which discover emergent events and corresponding CHs participate in data transmission, which means that TD-IMOCRP covers fewer nodes, especially when the sink is located at the corner. Therefore, it can help reduce node energy consumption and delay. Simulation results demonstrate that compared with representative event-driven clustering protocols, TD-IMOCRP can decrease the average number of covered nodes and the total energy consumption by more than 66.3% and 25%, respectively. In addition, when serving time-triggered traffic, TD-IMOCRP can achieve almost the same performance as its basic version IMOCRP which is better than majority of current time-triggered clustering protocols. In a word, TD-IMOCRP can guarantee in-time delivery of event-driven information while guaranteeing its performance of serving time-triggered traffic.

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks.

The rapid growth in wireless communications, coupled with insufficient utilization of the spectrum, led to the development of new wireless services and the promising technology of cognitive radio (CR) networks, which facilitate periodic access to the unoccupied spectrum bands and thus increases spectral efficiency. A fundamental task in CR networks is spectrum sensing, through which unauthorized secondary users (SUs) detect unoccupied bands in the spectrum. To achieve this, an accurate estimate of the power spectrum is necessary. From this perspective, and given that many other factors can affect individual detection, such as pathloss and receiver uncertainty, we aim to improve its estimate by exploiting the spatial diversity in the SUs' observations. Spectrum sensing is treated as a parameters estimation problem, assuming that the parameters' vector of each SU consists of some global and partially common parameters. To exploit this modeling, distributed and cooperative spectrum sensing is the subject of interest in this study. Diffusion techniques, and especially the Adapt-Then-Combine (ATC) method will be exploited, where each SU cooperates with a group of nodes in its neighborhood that share the same parameters of interest. We consider a network of three static PUs with overlapping power spectrums, and thus, frequency bands. The performance of the employed method will be evaluated under two scenarios: (i) when the PUs spectrum varies, since some frequency bands are not yet utilized, and (ii) when the frequency bands of the PUs are fixed, but there is a mobile SU in the network, changing regions and parameters of interest. Experimental results and performance analysis reveal the ATC algorithm robustness and efficiency.

A Radio Environment Map Updating Mechanism Based on an Attention Mechanism and Siamese Neural Networks.

A radio environment map (REM) is an effective spectrum management tool. With the increase in the number of mobile devices, the wireless environment changes more and more frequently, bringing new challenges to REM updates. Traditional update methods usually rely on the amount of data collected for updating without paying attention to whether the wireless environment has changed enough. In particular, a waste of computational resources results from the frequently updated REM when the wireless environment does not change much. When the wireless environment changes a lot, the REM is not updated promptly, resulting in a decrease in REM accuracy. To overcome the above problems, this work combines the Siamese neural network and an attention mechanism in computer vision and proposes an update mechanism based on the amount of wireless environmental change starting from image data. The method compares the newly collected crowdsourced data with the constructed REM in terms of similarity. It uses similarity to measure the necessity of the REM to be updated. The algorithm in this paper can achieve a controlled update by setting a similarity threshold with good controllability. In addition, the effectiveness of the algorithm in detecting changes of the wireless environment has been demonstrated by combing simulation data.

A Usage Aware Dynamic Spectrum Access Scheme for Interweave Cognitive Radio Network by Exploiting Deep Reinforcement Learning.

Future-generation wireless networks should accommodate surging growth in mobile data traffic and support an increasingly high density of wireless devices. Consequently, as the demand for spectrum continues to skyrocket, a severe shortage of spectrum resources for wireless networks will reach unprecedented levels of challenge in the near future. To deal with the emerging spectrum-shortage problem, dynamic spectrum access techniques have attracted a great deal of attention in both academia and industry. By exploiting the cognitive radio techniques, secondary users (SUs) are capable of accessing the underutilized spectrum holes of the primary users (PUs) to increase the whole system's spectral efficiency with minimum interference violations. In this paper, we mathematically formulate the spectrum access problem for interweave cognitive radio networks, and propose a usage-aware deep reinforcement learning based scheme to solve it, which exploits the historical channel usage data to learn the time correlation and channel correlation of the PU channels. We evaluated the performance of the proposed approach by extensive simulations in both uncorrelated and correlated PU channel usage cases. The evaluation results validate the superiority of the proposed scheme in terms of channel access success probability and SU-PU interference probability, by comparing it with ideal results and existing methods.

Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks.

Current modulation recognition methods in wireless sensor networks rely too much on simulation datasets. Its practical application effect cannot reach the expected results. To address this issue, in this paper we collect a large amount of real-world wireless signal data based on the software radio device USRP 2920. We then propose a real radio frequency (RF) database architecture and preprocessing operators to manage real-world wireless signal data, conduct signal preprocessing, and export the dataset. Based on different feature datasets derived from the RF database, we propose a multidimensional feature hybrid network (MFHN), which is used to identify unknown signals by analyzing different kinds of signal features. Further, we improve MFHN and design a multifeatured joint migration network (MJMN) to identify small-sample targets. The experimental results show that the recognition rates for unknown target signals of the MFHN and MJMN are 82.7% and 93.2%, respectively. The proposed methods improve the recognition performance in the single node of wireless sensor networks in complex electromagnetic environments, which provides reference for subsequent decision fusion.

Channel-Hopping Sequence and Rendezvous MAC for Cognitive Radio Networks.

In cognitive radio networks (CRNs), two secondary users (SUs) need to meet on a channel among multiple channels within a finite time to establish a link, which is called rendezvous. For blind rendezvous, researchers have devised ample well-grounded channel hopping (CH) sequences that guarantee smaller time-to-rendezvous. However, the best part of these works lacks the impact of network factors, particularly channel availability and collision during rendezvous. In this study, a new CH scheme is investigated by jointly considering the medium access control (MAC) protocol for single-hop multi-user CRNs. The analysis of our new variable hopping sequence (V-HS) guarantees rendezvous for the asymmetric channel model within a finite time. Although this mathematical concept guarantees rendezvous between two SUs, opportunities can be overthrown because of the unsuccessful exchange of control packets on that channel. A successful rendezvous also requires the exchange of messages reliably while two users visit the same channel. We propose a MAC protocol, namely ReMAC, that can work with V-HS and CH schemes. This design allows multiple rendezvous opportunities when a certain user visits the channel and modifies the conventional back-off strategy to maintain the channel list. Both simulation and analytical results exhibited improved performance over the previous approaches.

Modeling Radio Wave Propagation for Wireless Sensor Networks in Vegetated Environments: A Systematic Literature Review.

The use of wireless sensor networks (WSN) for monitoring variables in agricultural environments and natural forests has been increasing in recent years. However, the sizing of these systems is affected by the inaccuracy of the radio wave propagation models used, leading to possible increased costs and measurement errors. This systematic literature review (SLR) aims to identify propagation models widely used in WSN deployments in agricultural or naturally vegetated environments and their effectiveness in estimating signal losses. We also identified today's wireless technologies most used in precision agriculture (PA) system implementations. In addition, the results of studies focused on the development of new propagation models for different environments are evaluated. Scientific and technical analysis is presented based on articles consulted in different specialized databases, which were selected according to different combinations of criteria. The results show that, in most of the application cases, vegetative models present high error values when estimating attenuation.

Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network.

Multicasting is a basic networking primitive used in a wide variety of applications that is also true for cognitive radio-based networks. Although cognitive radio technology is considered to be the most promising technology to deal with spectrum scarcity, it relates to completely different aspects of networking and presents new challenges. For cognitive radio-based multicast sessions, it is important to use the spectrum efficiently by reducing the number of channels used as well as engaging fewer nodes in data relaying. This will benefit the network in three ways. First, it will decrease the number of transmissions. Second, it will help to reduce energy usage. Third, it will spare more channels and relay nodes for simultaneous multicast sessions. To achieve these advantages, efficient channel selection and relay nodes are required based on hop-to-hop communication. In this paper an algorithm has been developed that attempts to minimize energy consumption by selecting the minimum possible number of relay nodes and channels for a multicast session, taking into account the sporadic availability of the spectrum. The proposed method performs effectively compared to the flooding method in terms of energy consumption for the provided examples in multicasting.

Elite-CAM: An Elite Channel Allocation and Mapping for Policy Engine over Cognitive Radio Technology in 5G.

The spectrum allocation in any auctioned wireless service primarily depends upon the necessity and the usage of licensed primary users (PUs) of a certain band of frequencies. These frequencies are utilized by the PUs as per their needs and requirements. When the allocated spectrum is not being utilized in the full efficient manner, the unused spectrum is treated by the PUs as white space without believing much in the concept of spectrum scarcity. There are techniques invented and incorporated by many researchers, such as cognitive radio technology, which involves software-defined radio with reconfigurable antennas tuned to particular frequencies at different times. Cognitive radio (CR) technology realizes the logic of the utility factor of the PUs and the requirements of the secondary users (SU) who are in queue to utilize the unused spectrum, which is the white space. The CR technology is enriched with different frequency allocation engines and with different strategies in different parts of the world, complying with the regulatory standards of the FCC and ITU. Based on the frequency allocation made globally, the existing CR technology understands the nuances of static and dynamic spectrum allocation and also embraces the intelligence in time allocation by scheduling the SUs whenever the PUs are not using the spectrum, and when the PUs pitch in the SUs have to leave the band without time. This paper identifies a few of the research gaps existing in the earlier literature. The behavioral aspects of the PUs and SUs have been analyzed for a period of 90 days with some specific spectrum ranges of usage in India. The communal habits of utilizing the spectrum, not utilizing the spectrum as white space, different time zones, the requisites of the SUs, the necessity of the applications, and the improvement of the utility factor of the entire spectrum have been considered along with static and dynamic spectrum usage, the development of the spectrum policy engine aligned with cooperative and opportunistic spectrum sensing, and access techniques indulging in artificial intelligence (AI). This will lead to fine-tuning the PU and SU channel mapping without being hindered by predefined policies. We identify the cognitive radio transmitter and receiver parameters, and resort to the same in a proposed channel adaption algorithm. We also analyze the white spaces offered by spectrum ranges of VHF, GSM-900, and GSM-1800 by a real-time survey with a spectrum analyzer. The identified parameters and white spaces are mapped with the help of a swotting algorithm. A sample policy has been stated for ISM band 2.4 GHz where such policies can be excited in a policy server. The policy engine is suggested to be configured over the 5G CORE spectrum management function.