Design and development of the network interface, packets scheduling and interference mitigation schemes for LTE based femtocell networks / Sinan Ghassan Abid Ali Al-Nasir

Cellular networks face numerous challenges in providing services for indoor users.Therefore, femtocells are suggested as a solution to indoor coverage issues that macro cells have failed to address to date in cellular networks such as Global System for Mobile Communication (GSM), Universal Mobile Telecommunications System (UMTS), and Long Term Evolution (LTE). Although femtocells can provide various benefits for both operators and users, many technical challenges must be resolved for effective femtocell deployment in real environments. In this thesis, the network interface, the packet scheduling and the interference management challenges are investigated in order to address these issues with proper solutions. The network interface challenge is related to the integration of the femtocell in a cellular network such as LTE. The proposed solution is to deploy an IP Multimedia Subsystem (IMS) as an integration platform between the femtocell and the LTE cellular network. Thus, an IMS module has been implemented for signalling in a LTE-based femtocell network that contains both registration and invitation procedures. Based on this study, it has been observed that the integration of an IMS in a LTE based femtocell network can improve the network performance since the Packet Loss Ratio (PLR) can be minimised

Q-Learning vertical handover scheme in two-tier LTE-A networks

Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers

Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks

Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased

Automated Diagnosis of Childhood Pneumonia in Chest Radiographs Using Modified Densely Residual Bottleneck-Layer Features

Pneumonia is a severe infection that affects the lungs due to viral or bacterial infections such as the novel COVID-19 virus resulting in mild to critical health conditions. One way to diagnose pneumonia is to screen prospective patient’s lungs using either a Computed Tomography (CT) scan or chest X-ray. To help radiologists in processing a large amount of data especially during pandemics, and to overcome some limitations in deep learning approaches, this paper introduces a new approach that utilizes a few light-weighted densely connected bottleneck residual block features to extract rich spatial information. Then, shrinking data batches into a single vector using four efficient methods. Next, an adaptive weight setup is proposed utilizing Adaboost ensemble learning which adaptively sets weight for each classifier depending on the scores generated to achieve the highest true positive rates while maintaining low negative rates. The proposed method is evaluated using the Kaggle chest X-ray public dataset and attained an accuracy of 99.6% showing superiority to other deep networks-based pneumonia diagnosis methods

EPIdemiology of Surgery-Associated Acute Kidney Injury (EPIS-AKI) : Study protocol for a multicentre, observational trial

More than 300 million surgical procedures are performed each year. Acute kidney injury (AKI) is a common complication after major surgery and is associated with adverse short-term and long-term outcomes. However, there is a large variation in the incidence of reported AKI rates. The establishment of an accurate epidemiology of surgery-associated AKI is important for healthcare policy, quality initiatives, clinical trials, as well as for improving guidelines. The objective of the Epidemiology of Surgery-associated Acute Kidney Injury (EPIS-AKI) trial is to prospectively evaluate the epidemiology of AKI after major surgery using the latest Kidney Disease: Improving Global Outcomes (KDIGO) consensus definition of AKI. EPIS-AKI is an international prospective, observational, multicentre cohort study including 10 000 patients undergoing major surgery who are subsequently admitted to the ICU or a similar high dependency unit. The primary endpoint is the incidence of AKI within 72 hours after surgery according to the KDIGO criteria. Secondary endpoints include use of renal replacement therapy (RRT), mortality during ICU and hospital stay, length of ICU and hospital stay and major adverse kidney events (combined endpoint consisting of persistent renal dysfunction, RRT and mortality) at day 90. Further, we will evaluate preoperative and intraoperative risk factors affecting the incidence of postoperative AKI. In an add-on analysis, we will assess urinary biomarkers for early detection of AKI. EPIS-AKI has been approved by the leading Ethics Committee of the Medical Council North Rhine-Westphalia, of the Westphalian Wilhelms-University Münster and the corresponding Ethics Committee at each participating site. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and used to design further AKI-related trials. Trial registration number NCT04165369

Self-configuration Concept to Solve Physical Cell ID Conflict for SON LTE-based Femtocell Environment

and Self-healing functions are the most important concepts for self-managing heterogeneous network. However, the concept of self-configuration can be used to solve various challenges in the femtocell deployment phase and also in the PCIs confusion and collision problems. However, the proposed solutions for interference mitigation are not satisfying and need further improvement. Two main reasons identified for this unsatisfactory, firstly the small number of femtocells used in the simulation scenario which can lead to high failure probability if applied under real enterprise environment, secondly; the provided solutions discussed only part of the problem,i.e. either in co-tier interference or cross-tier interference but not both. Thus the need arises for stable solution which can resolve the interference problem for both inter and intra scenarios. In addition among the tree types of approaches used to solve collision and confusion problems the Nokia Siemens approach was the best. Index Terms — Self-configuration, cross-tire and co-tier interference, SON, LTE-femtocell, interference. I

Femtocell geo-location challenge DSL approach as solution

Femtocell or Home eNode cell in LTE is a home base station that anticipated to be deployed in very large numbers with fully automated manner. Femtocell provides enhanced coverage for in‐building cellular services. The enhanced data rates enable new multimedia services which in turn generate new revenue. However, with all the convenience such device can provide, locating the user’s geographic location represents a great deal of challenge for law enforcement and operators alike. In this work we propose a simple and direct approach that does not require any changes in the network or in the femtocell standard design by exploiting the connection between the femtocell and the network operator through the DSL backhaul. Result shows the proposed approach has achieved successfully the goal of locating the geographic location of the femtocell user precisely

New graph colouring algorithm for resource allocation in large-scale wireless networks

The vertex-colouring problem is a well-known classical problem in graph theory in which a colour is assigned to each vertex of the graph such that no two adjacent vertices have the same colour. The minimum vertex-colouring problem is known as NP-hard problem in an arbitrary graph. In this paper a graph colouring algorithm based on modified incidence matrix is proposed for resolving Physical Cell ID (PCI) allocation for largescale femtocell deployment in LTE Telecommunication Networks. The proposed algorithm is not specified for neighbours only, but additionally can deal with neighbours of neighbours’ objects due to telecommunication requirements. Our results show that by applying proper searching and assigning methods it is possible to achieve satisfactory results for resource allocation in large and complex networks such as resolving PCI allocation and conflict for large femtocells deployment in LTE Networks

EPIdemiology of Surgery-Associated Acute Kidney Injury (EPIS-AKI): Study protocol for a multicentre, observational trial

Introduction More than 300 million surgical procedures are performed each year. Acute kidney injury (AKI) is a common complication after major surgery and is associated with adverse short-term and long-term outcomes. However, there is a large variation in the incidence of reported AKI rates. The establishment of an accurate epidemiology of surgery-associated AKI is important for healthcare policy, quality initiatives, clinical trials, as well as for improving guidelines. The objective of the Epidemiology of Surgery-associated Acute Kidney Injury (EPIS-AKI) trial is to prospectively evaluate the epidemiology of AKI after major surgery using the latest Kidney Disease: Improving Global Outcomes (KDIGO) consensus definition of AKI. Methods and analysis EPIS-AKI is an international prospective, observational, multicentre cohort study including 10 000 patients undergoing major surgery who are subsequently admitted to the ICU or a similar high dependency unit. The primary endpoint is the incidence of AKI within 72 hours after surgery according to the KDIGO criteria. Secondary endpoints include use of renal replacement therapy (RRT), mortality during ICU and hospital stay, length of ICU and hospital stay and major adverse kidney events (combined endpoint consisting of persistent renal dysfunction, RRT and mortality) at day 90. Further, we will evaluate preoperative and intraoperative risk factors affecting the incidence of postoperative AKI. In an add-on analysis, we will assess urinary biomarkers for early detection of AKI. Ethics and dissemination EPIS-AKI has been approved by the leading Ethics Committee of the Medical Council North Rhine-Westphalia, of the Westphalian Wilhelms-University Münster and the corresponding Ethics Committee at each participating site. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and used to design further AKI-related trials. Trial registration number NCT04165369.