LTE Advanced

About: LTE Advanced is a research topic. Over the lifetime, 4055 publications have been published within this topic receiving 74262 citations. The topic is also known as: Long-Term Evolution Advanced & LTE-A.

Performance Analysis of Resource Scheduling Techniques in Homogeneous and Heterogeneous Small Cell LTE-A Networks

Abstract: The purpose of LTE-A technology is to provide high spectral efficiency, lower delay and stronger intercell interference control for a multi- user environment. The architecture of LTE basically contains E-UTRAN and evolved packet core. E-UTRAN is the combination of UE and ENodeB (enhanced node B) used to control the radio network. EPC provide end to end connection and backward capability with previous networks. Major entities included in EPC are P-GW, S-GW, HSS and MME. This new architecture fulfil the requirement of next-generation mobile networks for high connectivity and multiple type of networks. Heterogeneous network is one of them in which different power base stations like femtocell, picocell, and radio remote head deployed in a geographical area with in macrocell cell. It is one of the cost effective solution to provide high throughput and spectral efficiency and fairness for cell edge user. Deployment of femtocell improved the data rate and coverage in small regions like office, home, shopping mall and dense areas. Along with this an efficient fair sharing of resource allocation plays an important role in improving the performance of networks. This paper analysed the performance of round robin, resource fair, Max-throughput, best CQI and proportional fair LTE-A resource scheduling techniques on homogeneous networks. For heterogeneous networks a new cluster based proportional fair resource scheduling technique is proposed, which provides an efficient resource to the most sufferer user and improved fairness and cell edge user throughputs. In heterogeneous networks multiple femto cell were deployed in macro cell area. Access policies are applied on open and closed group. The performance is measured in terms of cell edge throughputs, peak throughputs, average throughputs, wideband SINR, spectral efficiency, and fairness index for homogeneous, heterogeneous networks and for user mobility. The performance result showed that Best CQI and MaxTP scheduler outperforms in throughput level and attains highest average cell throughput of 83 Mbps and UE average throughput of 20 mbps in homogeneous networks and approximately 43 Mbps in heterogeneous networks. Comparative result in heterogeneous network indicates that the proposed scheduler increases 2% gain in fairness and 1–1.89% gains in edge throughputs with respect to proportional fair scheduler and allocates 79% fair share resources among UE. Round robin scheduler delivered very poor throughput and fairness index in both homogeneous and heterogeneousnetworks.

Base Station Selection in M2M Communication Using Q-Learning Algorithm in LTE-A Networks

Abstract: A major problem faced by machine type communication (MTC) devices in machine to machine (M2M) communication is the congestion and traffic overloading when incorporating into LTE Advanced networks. In this paper, we present an approach to tackle this problem by providing an efficient way for multiple access in the network and minimizing network overload. We consider the random access network (RAN) between the LTE base stations and MTC devices in the cell. We propose an unsupervised learning algorithm, based on Q-learning, as a means of base station selection scheme where MTC devices continuously adapt to changing network traffic and decide which base station is to be selected on the basis of QoS parameters. Simulation results demonstrate that the proposed algorithm helps MTC devices achieve better performance and, therefore, enhances the M2M communication performance.

Exploration and comparison of different 4G technologies implementations: A survey

Abstract: Wireless networks avoid the installation costs incumbent in wired networks. Nowadays, users of mobile Internet have grown significantly and require instant accessibility of various high speed Internet applications. This paper presents a review of Fourth Generation (4G) networks and its evolution. A Long Term Evolution (LTE) network provides mobile Internet users with all-IP solutions and seamless connectivity. A detailed analysis of different 4G technologies e.g. WiMAX and LTE network is presented in this paper. In addition, this paper presents a discussion about the architecture of LTE network and various issues faced in LTE technology.

Power Saving Scheduling Scheme for Internet of Things over LTE/LTE-Advanced Networks

Abstract: The devices of Internet of Things (IoT) will grow rapidly in the near future, and the power consumption and radio spectrum management will become the most critical issues in the IoT networks. Long Term Evolution (LTE) technology will become a promising technology used in IoT networks due to its flat architecture, all-IP network, and greater spectrum efficiency. The 3rd Generation Partnership Project (3GPP) specified the Discontinuous Reception (DRX) to reduce device’s power consumption. However, the DRX may pose unexpected communication delay due to missing Physical Downlink Control Channel (PDCCH) information in sleep mode. Recent studies mainly focus on optimizing DRX parameters to manage the tradeoff between the energy consumption and communication latency. In this paper, we proposed a fuzzy-based power saving scheduling scheme for IoT over the LTE/LTE-Advanced networks to deal with the issues of the radio resource management and power consumption from the scheduling and resource allocation perspective. The proposed scheme considers not only individual IoT device’s real-time requirement but also the overall network performance. The simulation results show that our proposed scheme can meet the requirements of the DRX cycle and scheduling latency and can save about half of energy consumption for IoT devices compared to conventional approaches.

Multiuser MIMO Scheduling for LTE-A Downlink Cellular Networks

Abstract: In this paper, we investigate multiuser MIMO scheduling in LTE downlink cellular networks. We formulate the downlink LTE-A MIMO scheduling as a weighted sum rate maximization problem by allocating the RBs to users or user pairs subject to some constraints in LTE-A. We develop a low-complexity MU-MIMO scheduling and resource allocation algorithm and propose an adaptive switching approach between SU-MIMO and MU-MIMO to improve network performance. System-level simulation results demonstrate significantly performance improvement of the proposed MU-MIMO scheduling algorithm and the adaptive switching algorithm.