Performance analysis of long term evolution (LTE) network

University of Technology Sydney. Faculty of Engineering and Information Technology.The demand for high speed network has led to the development of LTE. The LTE replaced circuit switched legacy systems into packet switched network. The high speed simultaneous transmission of data is achieved by using Orthogonal Frequency Division Multiple Access (OFDMA) in the downlink. To achieve high speed multimedia services in the downlink various packet scheduling algorithms have been proposed in the past. The LTE architecture has been simplified compared to 2G or 3G systems to a greater extent. The network elements namely Base Station Controller (BSC) and Radio Network Controller (RNC) have been replaced with eNodeB. The Radio Resource Management (RRM) functionality has been confined to eNodeB. To enable end users to achieve high data rates Heterogeneous Networks (HetNets) are used. In HetNets, the pico cells and femto cells work alongside the macro cells to deliver the required QoS. The objective of this thesis is to study the performance of LTE network through simulation and by observing the KPIs from real-time network. The thesis starts with the performance analysis of downlink scheduling algorithms through simulations. The scheduling algorithms were simulated using NS-3 and LTE-Sim and various performance factors were studied. Thereafter, a model HetNet was simulated with a macro cell and pico cells. In the simulated LTE network environment, impact of pico cells on macro has been studied along with the scheduling algorithms. After simulations, a more practical approach has been taken to study the performance of the LTE network. The performance analysis of Proportional Fair (PF) scheduler has been made in the real-time LTE network. In this study, the end users were classified as Gold, Silver and Bronze based on the subscription plans. A combination of various scenarios has been was tested to analyse the throughput of the scheduler. Then the performance of RAN and Evolved Packet Core has been made by observing the Key Performance Indicators (KPIs). To obtain RAN KPIs drive tests were made in various modes such as walking around the city centre, travelling in train, driving in the car and in indoor environments. The KPIs were collected using Nemo Handy RF planning tool. The final part of the thesis covers the performance analysis of EPC. The KPIs such as accessibility, retainability, traffic, mobility, and Automatic Neighbour Relations (ANR) were collected for three months and the EPC performance was analysed. In the analysis, a critical issue in retainability was identified and this issue was impacting the accessibility of the network. After thorough analysis of KPIs, the root cause of the issue was identified as the Mobility Management Entity (MME) sending fake Serving Gateway (SGW) relocation request to eNodeB when there is only one SGW configured. This issue was identified and resolved using the KPIs

GROUP BASED ALGORITHM TO MANAGE ACCESS TECHNIQUE IN THE VEHICULAR NETWORKING TO REDUCE PREAMBLE ID COLLISION AND IMPROVE RACH ALLOCATION IN ITS

ABSTRACT Intelligent transportation system (ITS) is an application which provides intelligence to the transportation and traffic management systems. Although the word ITS applies to all systems in the transportation but as per the European union directive it is the application of Information and communication technology in the field of transportation is defined as ITS. The communication technology has evolved greatly today from 2G/3G to long term evolution (LTE). In this paper we focus on the LTE and its application in the ITS. Since LTE offers excellent QoS, wide area coverage and high availability it is a preferred choice for vehicle to infrastructure (V2I) service. At the same time the LTE customer base is increasing day by day which results in congestion and accessing the network to send or request resources becomes difficult. In this paper we have proposed a group based node selection algorithm to reduce the preamble ID collision otherwise this uncoordinated preamble ID transmission by vehicle node (VN) will eventually clog the network and there will be a massive congestion and re-transmissions attempts by VNs to obtain the random access channel (RACH). KEYWORDS Intelligent transportation system (ITS), Long term evolution (LTE), Mobile ad hoc network (MANET), Vehicle ad hoc network (VANET), Vehicle to infrastructure (V2I), Vehicle to vehicle (V2V), Random access channel (RACH)

SURVEY OF LTE DOWNLINK SCHEDULERS ALGORITHMS IN OPEN ACCESS SIMULATION TOOLS NS-3 AND LTE-SIM

ABSTRACT The LTE/LTE- KEYWORDS Round robin (RR), Proportional fair (PF), Maximum throughput scheduler (MT), Throughput to average scheduler (TTA), Blind equal throughput scheduler (BET), Token bank fair queue scheduler (TBFQ), Priority set scheduler (PS)

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049