Cellular Network Infrastructure Research Articles

Enhancing spectrum sensing efficiency in multi‐channel cognitive device‐to‐device networks: Medium Access Control layer strategies and analysis

AbstractThe detection and characterisation of electromagnetic signals within a specific frequency range, known as spectrum sensing, plays a crucial role in Cognitive Radio Networks (CRNs). The CRNs aim to adapt their communication parameters to the surrounding radio environment, thereby improving the efficiency and utilisation of the available radio spectrum. Spectrum sensing is particularly important in device‐to‐device (D2D) communication when operating independently of the cellular network infrastructure. The Medium Access Control (MAC) protocol coordinates device communication and ensures interference‐free operation of the CRN coexisting with the primary cellular network. A spectrum sensing strategy at the MAC layer for cognitive D2D communication. The strategy focuses on reducing the overall sensing period allocated at the MAC layer by having each Cognitive D2D User (cD2DU) sense a smaller subset of available channels while maintaining the same sensing time for cellular user detection at the physical layer. To achieve this, the concept of concurrent groups of D2D devices is introduced in proximity, which are formed by using unique IDs of cD2DUs during the device discovery stage. Each concurrent group senses a specific portion of the cellular user band in a shorter time, resulting in a reduced overall sensing period. In addition to mitigating traffic congestion through data diversion from the cellular network, the proposed strategy facilitates the concurrent sensing of multiple channels by cD2DUs within the underutilised cellular user band. This leads to extended data transmission periods, increased network throughput, and effective offloading of the cellular network. The effectiveness of the proposed work is evaluated by considering factors, such as network throughput and transmission time. Simulation results confirm the effectiveness of the approach in improving spectrum utilisation and communication efficiency in multi‐channel Cognitive D2D Networks (cD2DNs).

D2D Matching Techniques for Resource Allocation Management and Power Control Management in B5G/6G

The upcoming 6G network is expected to have a great integration of Device-to-Device (D2D) technology. One of the key advantages of D2D technology is its potential to minimize the load on cellular base stations, which can help extend the lifespan of cellular network infrastructure. D2D multicast communication can meet the growing demand for multimedia content in local area services by maximizing energy efficiency and device lifespan by reusing the same resources for the cellular network. In this paper, we investigate an efficient resource allocation scheme by using the One-To-Many Gale Shapley pairing algorithm (GSA) for efficient allocation and power optimization. We propose a joint optimization approach for D2MD clusters that considers the Signal-to-Interference Noise ratio and energy levels of devices' batteries. The problem is optimized, so it is divided into two convex sub-problems. In the first sub-problem, power allocation is performed for each candidate cluster-head (CH)and cellular user to maximize energy efficiency using the Dinkelbach matching algorithm. In the second sub-problem, the One-to-Many Gale Shapley matching algorithm is used to optimize resource allocation and cluster-head selection to select the Cluster Nodes (CRns) to form the cluster. Numerous investigations show that the suggested technique maintains QoS and minimal battery power requirements while increasing cluster-head longevity and energy efficiency (EE) in D2D applications.

Performance evaluation of pair selection algorithms in device-to-device communication using relay-assisted techniques

Communication services that are dependable are crucial, particularly during emergencies when the regular infrastructure for communication may be disrupted or nonexistent. In such situations, device-to-device (D2D) communication can be a helpful choice since it allows user equipment (UE) that is close to one another to connect directly, bypassing the cellular network infrastructure. The primary focus of this thesis is the application of D2D communication in a decentralized emergency scenario with a damaged eNodeB. The main objective is to find an appropriate strategy for finding and selecting D2D couples by simulating several methods in MATLAB. This study compares three D2D pair selection algorithms: distance-based, Signal-to-Interference and Noise Ratio (SINR)-based, and data rate-based distance-based. The simulation results show that the data rate-based strategy is the most effective method for selecting D2D couples in emergency scenarios. In contrast to algorithms that rely on distance and SINR, this one reduces the chance of an outage by 20%. Bit error rate (BER), capacity, spectral efficiency, and energy efficiency are the three types of links that are assessed: direct links, relay links, and UE relay links. The results show that, with the lowest BER and maximum data throughput, the direct link is the most reliable and efficient communication option. However, the relay connection and the UE relay link show better overall spectral efficiency in comparison to the direct link, indicating their ability to transport more data per unit of bandwidth. The option that consumes the least energy among the three is the direct link. The study demonstrates the great potential of D2D communication in emergency scenarios where conventional communication infrastructure may not be available. The direct link is the most dependable and effective alternative for communication, according to the data, although the UE link can still function effectively in the event that the direct link is compromised. The data rate-based method is a useful strategy for finding and choosing D2D partners. The results of this study can direct the development of D2D emergency communication solutions in 5G networks.

Advanced Intrusion Detection in Vehicular Networks: Empowering Security through Hybrid Off-loading Techniques and Enhanced Radial Bias Neural Network

Over the last several decades, the implementation of ITS has shown to be the most efficient and successful strategy for expanding the variety of current transportation networks. Vehicle-based offloading of data going to be essential for forthcoming networking innovations like D2D and 5G due to the substantial contribution it makes to efficiently using network capability while wasting minimal power. Information transmissions that would normally need a cellular network's infrastructure may instead be made using alternative networking mechanisms including Bluetooth, WiFi, and opportunistic communications. Data offloading has the ability to significantly increase the efficiency with which network resources are used. The offloading of data from vehicles has a considerable impact on the strain on cellular networks. It helps the network achieve higher throughput by facilitating the simultaneous reception of data by a large number of users. First, we must establish that the problem of Vehicular data offloading is an NP-hard target set selection (TSS) issue before we can even begin to characterize it. Using a combination of Hybrid PSO and GWO, TSS selects a small group of nodes to do the redundant data exchange (Particle Swarm Optimization with Gray Wolf Optimization). Collaboration between individuals and ISPs to identify effective aim sets may provide useful insights. If malicious users are present in the target group, they may slow down network activity by spoofing or by reducing the network's offloading capacity. It is possible that the whole network's performance would suffer as a direct result of these malicious users. In this study, we suggest a hybrid approach to communication for specifying the intended audience. We take use of the characteristics of opinion dynamics amongst users to get around the issue of overlapping community detection. Trust-based metrics inferred from users' activities are used to ensure the safety of the target set. In order to call 911, the suggested work additionally incorporates a method of sorting and classifying the offload limitations through Radial Bias Neural Network (RBNN). The following may be determined with the use of the proposed work's performance indicators: precision, entropy, and delay.

A novel enhanced security architecture for sixth generation (6G) cellular networks using authentication and acknowledgement (AA) approach

The sixth generation (6G) of cellular transmission is extremely adaptable. 6G will equip everyone with pervasive wireless connectivity and meet the needs of a fully connected world. It is anticipated that revolutionary ideas will increase in support for a fast-expanding variety of smart devices and applications. The sophisticated characteristics of 5G portable cellular network infrastructures produce novel threats and requirements. Comparing 6G cellular network technologies to 5G cellular networks, this paper discusses various security and privacy issues in 6G cellular networks based numerous security services. Proposes AA approach to evaluate the effectiveness of the methodology. Propose a new 6G wireless security architecture based on the analysis of secret key authentication and flexible position based identification, which serves as the foundation for an examination of identity management and flexible authentication. Demonstrates the benefits of the proposed architecture, analyzes BER against SINR and Measure Throughput Against various SINR values. Finally, Limitations and future recommendation for 6G cellular network security is presented.

Network Traffic Prediction with Reduced Power Consumption towards Green Cellular Networks

The increased number of cellular network subscribers is giving rise to the network densification in next generation networks further increasing the greenhouse gas emission and the operational cost of network. Such issues have ignited a keen interest in the deployment of energy-efficient communication technologies rather than modifying the infrastructure of cellular networks. In cellular network largest portion of the power is consumed at the Base stations (BSs). Hence application of energy saving techniques at the BS will help reduce the power consumption of the cellular network further enhancing the energy efficiency (EE) of the network. As a result, BS sleep/wake-up techniques may significantly enhance cellular networks' energy efficiency. In the proposed work traffic and interference aware BS sleeping technique is proposed with an aim of reducing the power consumption of network while offering the desired Quality of Service (QoS) to the users. To implement the BS sleep modes in an efficient manner the prediction of network traffic load is carried out for future time slots. The Long Short term Memory model is used for prediction of network traffic load. Simulation results show that the proposed system provides significant reduction in power consumption as compared with the existing techniques while assuring the QoS requirements. With the proposed system the power saving is enhanced by approximately 2% when compared with the existing techniques. His proposed system will help in establishing green communication networks with reduced energy and power consumption.

Traffic based power consumption and node deployment in green LTE-A cellular networks

The energy utilization of green cellular networking or cellular network infrastructure has become a popular research domain due to the economic concern of network operators and global climate change. Also, due to the growth of wireless networks, the authors are attracted to finding novel relay station (RS) deployment techniques to support high user density and high data rate services by reducing energy consumption and operating costs of different network elements. The location of RSs greatly influences how far a cell can be covered. Therefore, the deployment RS plays a major role in widening the cell's coverage radius. To solve these challenges and to realize greener network designs by maximizing power consumption with QoS assurance, a novel traffic-based power consumption minimization and node deployment for the LTE green cellular networks is proposed. Also, key performance indicators (KPIs) are required to monitor and improve network performance. KPIs control the accomplished resource utilization and the quality of services. The research work comprises RS deployment, traffic estimation, and power allocation. Power losses, communication delays, increased implementation costs, and decreased throughput are the effects of an inappropriate RS deployment. Therefore, this research introduces the transmission area-based relay stations deployment scheme (TARSD) with multiobjective functions maximization of coverage area, minimization of the overlapping area and the minimization of power consumption cost. Traffic estimation helps to identify future capacity requirements and enables improved planning and decision-making. The deployment scheme of a cellular network relies on network traffic estimation. Nash traffic entropy learning algorithm (NTEL) is used to estimate traffic, and based on the estimated eNB switching ON/OFF is performed to minimize power consumption. Inter cell interference (ICI) can impact the performance of the LTE network. Several power allocation schemes can be used to improve system performance to achieve the optimal trade-off between interference and signal-to-noise ratio (SINR). Because of its good performance and efficacy in improving the mutual information between a channel's input and output, the enhanced low complexity water-filling (ELCWF) has been widely employed in power allocation with its increment and decrement properties. This research studies the statistical behaviour of a Received Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Signal to Interference noise Ratio (SINR). Also, statistical analysis of cost versus coverage performance is examined. Under the 7th simulation run, the proposed method yields the best coverage of 88.81 and 98.74%, respectively. In the experimental scenario, for the proposed model, the deployment cost for BS and RS are 27 and 13 units, the average throughput per user is 9.74 Mbps, and the coverage ratio is 97% under the BS candidate location of 20, respectively. In the power allocation stage, if the number of users is 50, the proposed model yields a power consumption of 0.2 W, throughput of 23.4 Mbps, delay of 15 ms and SINR of 20.12 dB, respectively.

Collaborative Orchestration of Multi-Domain Edges From a Connected, Cooperative and Automated Mobility (CCAM) Perspective

The 5G ecosystem is comprised of the cellular 5G System, as well as a managed and orchestrated infrastructure providing virtualized network and service functions. The automotive industry with its stringent requirements for connected vehicles is a promising and yet challenging consumer of such 5G ecosystem. Deployment of service instances at distributed cloud resources of cellular network infrastructure edges enables localized low-latency access to these services from moving vehicles but comes along with challenges, such as the need for fast reconfiguration of the distributed deployment according to mobility pattern and associated service and resource demand. In this paper, we investigate a solution for the collaborative orchestration of services for Connected, Cooperative and Automated Mobility (CCAM) within such 5G ecosystem. A key objective is the service continuity for a highly dynamic automotive scenario, achieved by the associated management and orchestration of these services in distributed edge clouds. The proposed solution leverages a multi-tier orchestration system as well as localized management and protocol operations for collaborative edge resources. By means of both analytical and experimental evaluations, the paper draws conclusions on the gain in accelerating orchestration decisions and enforcements, while balancing associated protocol and computational load over the highly distributed and multi-layered orchestration system.

Insecurity of Operational IMS Call Systems: Vulnerabilities, Attacks, and Countermeasures

IMS (IP Multimedia Subsystem) is an essential 4G/5G component to offer multimedia services. It is used worldwide to support two call services: VoLTE (Voice over LTE) and VoWiFi (Voice over WiFi). In this study, it is shown that the signaling and voice sessions of VoWiFi can both be hijacked by a malicious adversary. By hijacking the signaling session, s(he) gains the ability to make ghost calls to launch stealthy DoS (Denial of Service) or caller-ID spoofing attacks against specific cellular users. Such attacks can be carried out without any malware or network information, and require only the victim’s phone number to be known. It is shown that phones vulnerable to the call DoS attacks can be detected at run time by exploiting a vulnerability of cellular network infrastructures referred to as call information leakage, which is exposed based on a machine learning method. Especially, the call DoS attacks can prevent victims from receiving incoming calls for up to 99.0% time without user awareness. Moreover, by hijacking the voice session, an adversary can launch stealthy free data transfer attacks based on phone numbers alone rather than IP addresses. The identified vulnerabilities/attacks are validated in the operational 4G networks of four top-tier carriers across Asia and North America with seven phone brands. The study concludes by presenting a suite of solutions to address them.

On Scalable Network Communication for Infrastructure-Vehicle Collaborative Autonomous Driving

Network communication is crucial for Infrastructure-Vehicle Cooperative Autonomous Driving (IVCAD), which can help to improve both driving safety and efficiency. Existing IVCAD systems either use RoadSide Units (RSUs) deployed sparsely in critical locations to extend the on-board sensing, or use RSUs deployed densely in a limited area to provide both sensing and decision-making for vehicles. For both scenarios, the numbers of RSUs and vehicles are small, and the network communication solutions are based on the existing wireline and cellular network infrastructures and their extensions. However, it remains unknown whether these existing network communication solutions are scalable when the IVCAD system is deployed city-widely with hundreds of thousands of RSUs and millions of vehicles. In this paper, we analyze the network communication requirements for different types of IVCAD systems, and show that when the numbers of RSUs and vehicles in the system are large, using the existing solutions to support IVCAD can incur very high extra network communication facility cost. We further discuss how to use wireless mesh networks formed by RSUs themselves to solve the network communication problem without any deployment of extra network communication facilities. To enable the RSU network, we provide a network communication framework based on network coding and highlight some research directions.

Enhancement of cellular networks via an improved clustering technique with D2D communication for mission-critical applications

In disasters, whether natural or man-made, establishing a wireless network to recover the damaged or destroyed cellular network infrastructure is very important to save lives. Network throughput and power consumption are critical factors when designing such a wireless network. It is essential to ensure that the network can connect all people with the optimum ability to handle information traffic while utilizing less energy. The conventional clustering (CC) technology with D2D communication has enhanced the efficiency and power consumption of a wireless network. In disaster circumstances, however, using CC continues to be a challenge in ensuring that all user devices (UEs) can join the cluster. In this respect, this paper presents an approach termed Cluster Formation and Cluster Head Selection (CFACHS) to ensure that all UEs in the area affected have joined a cluster. CFACHS also targets enhancing the wireless network performance in terms of its throughput and power consumption. CFACHS partitions each cluster into two groups named Main Cluster (MC) with its Main Cluster Head (MCH) and a Sub-Cluster (SC) with its Sub-Cluster Head (SCH). In order to route the information, an algorithm named MCHs multi-hop routing path has been developed and implemented. Extensive simulation experiments were conducted using MATLAB to compare the performance of CFACHS with CFACHS without-SC and CC in terms of the network’s capacity and power consumption. The results reveal that CFACHS was advantageous in minimizing network power consumption, increasing power efficiency by 27.97% and 25.54% sequentially. Also, CFACHS enhanced network capacity by 7.8125% and 11.875%, respectively.

Modeling Cellular Network Infrastructure in SUMO

Communication networks are becoming an increasingly important part of the mobility system. They allow traffic participants to be connected and to exchange information related to traffic and roads. The information exchange impacts the behavior of traffic participants, such as the selection of travel routes or their mobility dynamics. Considering infrastructure-based networks, the information exchange depends on the availability of the network infrastructure and the quality of the communication links. Specifically in urban areas, today’s 4G and 5G networks deploy small cells of high capacity, which do not provide ubiquitous cellular coverage due to their small range, signal blocking, etc. Therefore, the accurate modeling of the network infrastructure and its integration in simulation scenarios in microscopic traffic simulation software is gaining relevance. Unlike traffic infrastructure, such as traffic lights, the simulation of a cellular network infrastructure is not natively supported in SUMO. Instead, the protocols, functions and entities of the communication system with the physical wireless transmission are modeled in a dedicated and specialized network simulator that is coupled with SUMO. The disadvantage of this approach is that the simulated SUMO entities, typically vehicles, are not aware which portions of the roads are covered by wireless cells and what quality the wireless communication links have. In this paper, we propose a method for modeling the cellular infrastructure in SUMO that introduces a cellular coverage layer to SUMO. This layer models cell sites in a regular hexagonal grid, where each site is served by a base station. Following commonly accepted guidelines for the evaluation of cellular communication system, the method facilitates standardized and realistic modeling of the cellular coverage, including cell sites, antenna characteristics, cell association and handover. In order to ease the applicability of the method, we describe the work flow to create cell sites. As a representative case, we have applied the method to InTAS, the SUMO Ingolstadt traffic scenario and applied real data for the cellular infrastructure. We validate the approach by simulating a Cellular V2X system with sidelink connectivity in an urban macro cell environment by coupling SUMO enhanced by the proposed connectivity sublayer with ARTERY-C, a network simulator for Cellular V2X. As a proof-of-concept, we present a signal-to-interference noise ratio (SINR) coverage map and further evaluate the impact of different types of interference. We also demonstrate the effect of advanced features of cellular networks such as inter-cell interference coordination (ICIC) and sidelink communication modes of Cellular V2X with dynamic switching between the in-coverage and out-of-coverage mode.

Lightweight and Secure Authentication Model for Vehicle to Everything (V2X) Communication Based on 5G Networks

Integrating the cellular network infrastructure into Intelligent Transport Systems (ITS) received attention from the research community and standards groups. This technology allows the invention and development of new applications, as well as the development of new vehicle mobility solutions and the enhancement of driver mobility in terms of safety, reliability, capacity, and quality. Cellular communications networks such as LTE-V2X and 5G NR, integrated into the Vehicle to Everything (V2X) architecture designed to support vehicular communications and deployed on a large scale, appear in particular to be a relevant solution. They could indeed guarantee reliable geographic distribution and acceptable performance (latency, bandwidth, packet loss). In this context, we propose a secure authentication scheme for 5G-based V2X communication. To achieve security requirements, our approach aims to provide a high degree of security in different vehicular communication (V2V, V2I, V2N) by using lightweight cryptographic algorithms in order to safely receive all keys and messages from RSU, vehicles, and the network. To validate our approach, we use the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool to achieve the security goals, also evaluate the performance according to the operational cost which demonstrates that our model has a less computational cost.

OBSERVATION SYSTEM RESOURCE PLANNING IN PRESENCE OF ACCESS CONTROL BASED ON VOLUME OF RESOURCE OCCUPIED BY TRAFFIC FLOWS

Due to various recent improvements in cellular technology, communication networks now offer information flows with a wide range of transmission speed and service quality characteristics. These characteristics are more highly noticeable in intelligent networks, particularly when IoT technology is used. Regulation and high-quality transmission of such massive volumes of data present severe issues among virtual operators engaged in the communications sector and utilizing cellular network infrastructure to provide video surveillance services for its consumers. Unfortunately, no single approach exists that enables the execution of high-quality incoming traffic flow maintenance and the allocation of information transmission resources in diverse networks. One of the methods to address these issues is mathematical modelling, which takes into consideration the unique characteristics of traffic flows that emerge and are approved for servicing. Our work addresses this problem by designing a resource allocation strategy for an isolated LTE network cell with heterogeneous traffic flows while sharing its radio resources. Traffic sources considered are operator surveillance system's video cameras that use cellular network infrastructure to deliver data to analytical centers. A mathematical model is used to study the process of sharing a resource, which takes into consideration the priority of real-time traffic, the elasticity property during file transfer, and the access restriction for all threads, based on the quantity of resource held by each thread. When sharing the resources of an isolated LTE network cell with heterogeneous traffic flows. Traffic sources are surveillance system operators' video cameras that use cellular network infrastructure to deliver data to analysis centers. Algorithms for evaluating the characteristics of the service of applications are constructed and the dependence of the characteristics on the restriction of access is investigated. Using the developed model, a scenario of dynamic distribution of the access node resource between incoming sessions has been developed, which allows creating conditions for differentiated servicing of heterogeneous traffic flows based on access restrictions and resource loading by each of the considered flows.

Energy-Constrained Computation Offloading in Space-Air-Ground Integrated Networks Using Distributionally Robust Optimization

With the rapid development of connecting massive devices to the Internet, especially for remote areas without cellular network infrastructures, space-air-ground integrated networks (SAGINs) emerge and offload computation-intensive tasks. In this paper, we consider a SAGIN, where multiple low-earth-orbit (LEO) satellites providing connections to the cloud server, an unmanned aerial vehicle (UAV), and nearby base stations (BSs) providing edge computing services are included. The UAV flies along a fixed trajectory to collect tasks generated by Internet of Things (IoT) devices, and forwards these tasks to a BS or the cloud server for further processing. To facilitate efficient processing, the UAV needs to decide where to offload as well as the proportion of offloaded tasks. However, in practice, due to the variability of environment and actual demand, the amount of arrival tasks is uncertain. If the deterministic optimization is utilized to develop offloading strategy, unnecessary system overhead or higher task drop rate may occur, which severely damages the system robustness. To address this issue, we characterize the uncertainty with a data-driven approach, and formulate a distributionally robust optimization problem to minimize the expected energy-constrained system latency under the worst-case probability distribution. Furthermore, the distributionally robust latency optimization algorithm is proposed to reach the sub-optimal solution. Finally, we perform simulations on the real-world data set, and compare with other benchmark schemes to verify the efficiency and robustness of our proposed algorithm.

Intelligent data processing methods in sensor networks of mobile and autonomous objects

In the near term, tasks related to monitoring mobile geographically distributed objects with the aim of efficiently managing them are acquiring great importance. An example of such tasks is the monitoring the state of given number of vehicles of agricultural enterprise, when it becomes necessary to promptly transfer given amount of data with high requirements for the level of their reliability. The use of the infrastructure of cellular mobile networks for this is not suitable for a number of reasons for rural areas. The paper proposes an approach based on the use of high-speed dynamic sensor networks. This makes it possible to carry out relay transmission of data between objects, including mobile ones. However, the issues of building flexible data transfer protocols in networks of this kind, providing a significant data transfer rate and taking into account the priority of the transmitted information and its features, still remain open. At the same time, for mobile objects in conditions of non-stationarity of the parameters of communication channels, the problems of ensuring the required reliability of data are of particular importance. To solve the last problem, it is proposed to use the permutation decoding method based on the cognitive metaphor.

A Study on the Recital Necessities and Challenges of the 5th Generation Wireless Networks

In the ever-changing digital era, everybody enjoys speed, and more so speedy internet connections. Therefore, as most major telecom service providers are operating around the clock to develop internet connections even faster. The electronic devices human beings have become so dependent on such as smartphones, homes, cars, laptops and watches need stable internet connections. All these innovations require always-on and high-speed internet. The fifth generation (5G) wireless network couldn't have come at a much better time as devices and vehicular needing such strong connectivity are explosion every nanosecond and there is more technological progress. Taleb (2017) opine that the cellular network infrastructure is seen as one of the missing pieces needed to accelerate the optimization of the existing technology available today. 5G technology promises a future of improved data rates, quality service, decreased latency and improved capacity. It promises recital necessities which will be discussing in the paper under the sustainability and efficiency requirements.  The paper will also discourse the challenges that the 5G mobile network architecture faces in its journey to bring the fastest internet connectivity ever seen.

Recent Advances in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) represent a featured domain of wireless networks, which are well-differentiated from cellular network infrastructure and have attracted decades of research effort [...]

RIC: A RAN Intelligent Controller Platform for AI-Enabled Cellular Networks

With the emergence of 5G, network densification, and richer and more demanding applications, the radio access network (RAN)—a key component of the cellular network infrastructure—will become increasingly complex. To tackle this complexity, it is critical for the RAN to be able to automate the process of deploying, optimizing, and operating while leveraging novel data-driven technologies to ultimately improve the end-user quality of experience. In this article, we disaggregate the traditional monolithic control plane (CP) RAN architecture and introduce a RAN Intelligent Controller (RIC) platform decoupling the control and data planes of the RAN driving an intelligent and continuously evolving radio network by fostering network openness and empowering network intelligence with AI-enabled applications. We provide functional and software architectures of the RIC and discuss its design challenges. We elaborate how the RIC can enable near-real-time network optimization in 5G for the dual-connectivity use case using machine learning control loops. Finally, we provide preliminary results to evaluate the performance of our open-source RIC platform.

Tele-Healthcare Monitoring System-Based for the Management of Diabetes Emergencie

Introduction: Diabetes mellitus is a global health burden whose prevalence is increasing worldwide. Remote patient monitoring, an automated process which involve transmission of data swiftly from the person with diabetes to the health care providers is often considered to be a technological solution to the challenges of health care delivery with potential of reducing both morbidity and mortality. While the use of telehealth in diabetes management is becoming more prominent, however its use in the management of diabetes emergencies is not very common. Objective: To evaluate telehealth intervention in the management of patient with diabetes in the emergency setting with resultant early diagnosis and management. Methods: This paper presents a design, implementation and evaluation of Tele-healthcare monitoring system with the aids of GPS, smartphone and cellular network infrastructure to monitor patients with diabetes especially during diabetic emergencies. This system depends on remote monitoring of patient when away from the place of domicile or their treating doctor or family members using patient’s data. Patient can also be linked to nearby hospitals using GPS and the attending doctors would have access to patient’s data. Alarm is also issued by the system to the next-of-kin/family members or care giver by sending emergency SMS including the location, time and patient’s clinical condition. The developed system consists of mobile application and web based application. The Mobile application was developed with JAVA programming language and SQLite database. Results: The result from the evaluation of the developed system shows effectiveness of 83.33% and mean users’ perception of 94%. Conclusion: This system is simple and cost-effective to be implemented and enables early intervention when the blood glucose is abnormally high or low in order to save life of the patient without delay.