AI leverage in easing the 5G complexity and enhancing 5G intelligent connectivity

As 5G era is approaching fast and pre-commercial 5G tests and trials are happening everywhere around the world, one of the key challenges for carriers and 5G providers is to maintain and operate the network complexity required to meet diverse services and personalized user experience requirements. This maintenance and operation have to be smarter and more agile in 5G than it was in previous generations. AI and ML can be leveraged in this case to ease 5G complexity and at the same time enhance the intelligent connectivity between diverse devices and diverse tiny end points, e.g. IoT sensors. Machine learning and AI algorithms can be used to digest and analyse cross-domain data that would be required in 5G in a much more efficient way enabling quick decision and as such easing the network complexity and reducing the maintenance cost. The cross-domain data includes geographic information, engineering parameters and other data to be used by AI and ML to better forecast the peak traffic, optimize the network for capacity expansion and enable more intelligent coverage through dynamic interference measurements. This paper provides an overview of 5G complexity due to its heterogeneous nature and the key role of AI and ML to ease this complexity and enhance the intelligent connectivity between diverse devices with different requirements. The focus of this paper will be on the key aspects of AI and ML application in 5G and the key benefits from this application. Finally, this paper will analyse the overall performance of 5G in terms of coverage and latency compared with traditionally operated networks

NB-IoT: A Network slice for Massive IoT

Network virtualisation is a concept that has been around for some time now, but the concept of network slicing is more recent and only started to be mentioned in the context of 5G. In essence, network slicing is a specific form of network virtualisation that enables sharing of physical resources by multiple logical network slices used to serve different applications and use cases. One such a use case would be to allocate network resources to small things, e.g. sensors and very low power consumption objects. To allow these small objects access to network resources or to a slice of such resource, a new technology known as NB-IoT is being developed by different industry players. This paper provides an overview of NB-IoT technology and Network Slicing concept and how this concept is applied to allocate network resources to very tiny objects and things. Finally, this paper will analyse the overall performance of NB-IoT in terms of power saving and battery life using eDRX saving mechanism

Internet of Things: From applications, challenges and standardization to Industry implementations

The Internet of Things that is defined as anything that can be accessible anytime and anywhere provides connectivity to different objects and sensors around us and which will enable the transfer of different data between these objects and devices. A thing in the Internet of Things can be any natural or man-made object that can be assigned an IP address with a capability to exchange date over a network. There is a huge number of applications of IoT to benefit users, such as health monitors, smart homes, connected cars etc. If everything around us is connected and information about these things that can contain sensitive information, e.g. health and other personal information, are collected then these networks become very important and must be able to provide a proper security and privacy. It is believed that by 2020 there will be over 50 billion things that could be connected to Internet. Internet of things are very much associated with M2M (machine to machine communication) that is identified as a technology that makes objects smart, like smart homes, smart utility meters etc. M2M actually is considered to be a subset of IoT and which is mainly used for difficult and dangerous tasks, e.g. nuclear plants, etc. The deployment of IoT has already started and is expected to transform the way we live. According to Gartner, a technology research company, the Internet of Things has just reached the deployment stage by early adopters and the full deployment is expected in over ten years. From an industry angle, this paper will examine the market and technical trends of Internet of Things, main applications that will be supported by this technology, key issues and challenges faced by the industry, standards activities around IoT and finally the implementation landscape

Internet of Things: From applications, challenges and standardization to Industry implementations

The Internet of Things that is defined as anything that can be accessible anytime and anywhere provides connectivity to different objects and sensors around us and which will enable the transfer of different data between these objects and devices. A thing in the Internet of Things can be any natural or man-made object that can be assigned an IP address with a capability to exchange date over a network. There is a huge number of applications of IoT to benefit users, such as health monitors, smart homes, connected cars etc. If everything around us is connected and information about these things that can contain sensitive information, e.g. health and other personal information, are collected then these networks become very important and must be able to provide a proper security and privacy. It is believed that by 2020 there will be over 50 billion things that could be connected to Internet. Internet of things are very much associated with M2M (machine to machine communication) that is identified as a technology that makes objects smart, like smart homes, smart utility meters etc. M2M actually is considered to be a subset of IoT and which is mainly used for difficult and dangerous tasks, e.g. nuclear plants, etc. The deployment of IoT has already started and is expected to transform the way we live. According to Gartner, a technology research company, the Internet of Things has just reached the deployment stage by early adopters and the full deployment is expected in over ten years. From an industry angle, this paper will examine the market and technical trends of Internet of Things, main applications that will be supported by this technology, key issues and challenges faced by the industry, standards activities around IoT and finally the implementation landscape

Enabling technologies for 5G: Small Cells, massiveMIMO, mmWave, Network Slicing and Beamforming

With 5G is expected to be the most promising and probably the most complex technology in the market that has raised the hopes of a number of industries, standards bodies and vertical markets. The full development and deployment of 5G will be possible only after the development of a number of wireless and wireline-based technologies that are crucial and can be considered to be the enablers of 5G. These enabling technologies are Small Cells, massiveMIMO, mmWave, Network Slicing and Beamforming. These technologies will help 5G meet its requirements and expectation to integrate several old and new technologies, scenarios and use cases within an ecosystem with the sole purpose to enhance user experience by achieving shorter latency, more capacity and improved energy and frequency efficiency. The focus of this paper is on these enabling technologies, methods and approaches used to address the needs and requirements of 5G and the challenges ahead that stakeholders will be faced with

5G Testbed building and implementation as a form to support and drive Research and Innovation

Testing and feeling the capabilities of a real 5G network, but on a smaller scale is possible only through a 5G Testbed within a private setup, such as a university campus or a private site. This type of 5G Testbeds allow academics, researchers and students to test and experiment with the features and capabilities of novel designs and solutions with very rigid technical requirements, i.e. very high bandwidth, high density and very low latency. It helps to create a platform that would enable the customization and benchmarking of different prototypes for different use cases and scenarios. In addition, this paper will also highlight potential challenges and difficulties during the Testbed building and setup

5G Network Deployment at UBT: Features, capabilities and challenges

In this work, we describe our experience in deploying a 5G network at UBT targeting different 5G use cases through the virtualization of the underlying infrastructure. This paper describes the features and capabilities of the 5G network followed by the description of the challenges we faced while building this network, which could require further study and will open up new research opportunities in this space. The purpose of this deployed network is to allow students, researchers and academics to test and experiment with the features and capabilities of novel designs and solutions with very rigid technical requirements, i.e. very high bandwidth and very low latency by using network slicing and multi-access edge computing (MEC).. It helps to create a platform that would enable the customization and benchmarking of different prototypes for different use cases and scenarios. Furthermore, this paper will highlight the intention to continue to use the network for more bandwidth-hungry applications, such as the integration of immersive technologies with 5G and the enhancement of the user experience through the immersive technologies

World Journal of Gastroenterology ISSN 1007-9327

doi:10.3748/wjg.14.593

Symptomatic subserosal gastric lipoma successfully treated with enucleation

Gastric lipomas are rare tumors, accounting for 2%-3% of all benign gastric tumors. They are of submucosal or extremely rare subserosal origin. Although most gastric lipomas are usually detected incidentally, they can cause abdominal pain, dyspeptic disorders, obstruction, invagination, and hemorrhages. Subserosal gastric lipomas are rarely symptomatic. There is no report on treatment of subserosal gastric lipomas in the English literature. We present a case of a 50-year-old male with symptomatic subserosal gastric lipoma which was successfully managed with removal, enucleation of lipoma, explorative gastrotomy and edge resection for histology check of gastric wall. The incidence of gastric lipoma, advanced diagnostic possibilities and their role in treatment modalities are discussed