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.

Reinforcement learning based radio resource scheduling in LTE-advanced

Abstract: In this paper, a novel radio resource scheduling policy for Long Term Evolution Advanced (LTE-A) radio access technology in downlink acceptance is proposed. The scheduling process works with dispatching rules which are various with different behaviors. In the literature, the scheduling disciplines are applied for the entire transmission sessions and the scheduler performance strongly depends on the exploited discipline. Our method provides a straightforward schedule within transmission time interval (TTI) frame. Hence, a mixture of disciplines can be used for each TTI instead of the single one adopted across the whole transmission. The grand objective is to bring real improvements in terms of system throughput, system capacity and spectral efficiency (operator benefit) assuring in the same time the best user fairness and Quality of Services (QoS) capabilities (user benefit). In order to meet this objective, each rule must to be called on the best matching conditions. The policy adoption and refinement are the best way to optimize the use of mixture of rules. The Q-III reinforcement learning algorithm is proposed for the policy adoption in order to transform the scheduling experiences into a permanent nature, facilitating the decision-making on which rules will be used for each TTI. The IQ-III reinforcement learning algorithm using multi-agent environments refines the policy adoption by considering the agents' opinions in order to reduce the policy convergence time.

Quasi-Quadrature Modulation Method for Power-Efficient Video Transmission Over LTE Networks

Abstract: New emerging services, such as real-time video streaming or video on demand, are causing rapid growth in packet transmission over wireless networks. Unlike voice calls, for which the duration is usually not very long, video streaming applications require continuous transmission for a long time. Therefore, video streaming applications in mobile networks consume more energy compared with voice calls. Thus, the task of optimizing data transmission algorithms has become more important during the last few years. Apparently, the majority of multimedia traffic is video transmission. These applications consume much more power, compared with audio or general data transmission, because of higher throughput requirements. This paper addresses the problem of decreasing power consumption due to video transmission applications in Long-Term Evolution (LTE) networks. There are existing solutions for managing power consumption during video transmission. In particular, Third-Generation Partnership Project LTE Advanced (LTE-A) has defined the discontinuous reception/transmission (DRX/DRT) mechanism to allow devices to turn off their radio interfaces and go to sleep in various patterns. Some other similar solutions suggest DRX/DRT optimization to maximize the sleep periods of devices while guaranteeing quality of service in multimedia applications. However, existing solutions for packet transmission optimization are not very effective without physical-layer optimization. However, existing solutions for packet transmission optimization are not very effective without physical-layer optimization. We suggest a new method of modulation for improving energy efficiency of wireless video transmission. Four different schemes of quasi-quadrature modulation using multiple-input–multiple-output (MIMO) techniques with different quality of service performances are proposed in this paper. We simulate H.264/AVC video transmission. Results confirm the theoretical analysis. The proposed approach is able to improve energy efficiency while providing the same packet loss probability.

A Femto-Aided Location Tracking Algorithm in LTE-A Heterogeneous Networks

Abstract: In dense urban or indoor environments under a weak global positioning system (GPS) signal, the Long-Term Evolution Advanced (LTE-A) system can provide range measurements for location estimation of mobile stations (MSs). Based on the reference signals transmitted from macro base stations (mBSs), femto BS (fBSs), and neighbor MSs in LTE-A heterogeneous networks (HetNets), the femto-aided cooperative location tracking (FACLT) algorithm is proposed to estimate an MS's position. Since fBSs are user-deployed in the residential or business buildings, the locations of fBSs are usually not known exactly. Moreover, an MS can communicate with its neighbor MSs with the support of device-to-device (D2D) communications. To deal with the uncertain neighbor MSs' positions and the imprecise fBSs' positions, we utilize a Bayesian framework to investigate a distributed cooperative location tracking problem and a particle filter (PF) to develop the FACLT algorithm. Different femto-aided strategies are adopted to deal with the uncertainty of fBS position. The utilization of the PF not only allows the fusion of time difference of arrival (TDOA) and two-way time of arrival (TW-TOA) measurements but enables the line-of-sight (LOS)/non-LOS (NLOS) condition as well, based on the information of the Markov model or indoor map. Performance evaluation is conducted based on the system-level simulation of LTE-A HetNet environments, where the proposed FACLT algorithm using the assistive fBSs and cooperative MSs provides better location tracking of MSs.

Service continuity for eMBMS in LTE/LTE-advanced network: Standard analysis and supplement

Abstract: Evolved Multimedia Broadcast Multicast Service (eMBMS) has recently attracted a great attention from the telecommunication industry. All big companies in the field have invested and intended to deploy eMBMS as the broadcast solution in response to the immense demand in multimedia traffic. The eMBMS, also known as LTE broadcast, can provide high quality live video streaming services for a large number of users simultaneously in an open area such as a stadium or arena during an entertainment or sport event. Nowadays, in a high mobility environment, maintaining the service reception for moving users becomes a crucial task for mobile operators and service providers. Unfortunately, the support from LTE standard for eMBMS service continuity is very limited at the moment and in many cases, the users cannot continue to receive their desired services. To overcome the limitation in the standard, this paper will present a novel method to ensure the service continuity as well as to reduce the service interruption time during handover period for eMBMS users in the mobility context.

Channel estimation for LTE downlink in High Altitude Platforms (HAPs) systems

Abstract: We describe in this paper, channel estimation performance evaluation of Long Term Evolution (LTE) downlink that uses Orthogonal Frequency Division Multiplexing (OFDM) technique, which employs High Altitude Platforms (HAPs) as radio communication channel. HAPs have advantages due to unique altitude position between terrestrial and satellite systems and hence promising as alternative candidate for radio communication channel in the future. LTE is predecessor of LTE Advanced that has been selected as Fourth Generation (4G) of mobile communication systems. Channel estimation is the vital part of receiver if the system uses coherent and multi-level demodulation. Therefore, we choose two estimation methods, Least Square (LS) and Linear Minimum Mean Square Error (LMMSE), to evaluate the performance in term of Mean Square Error (MSE) and Bit Error Rate (BER) versus Signal Noise to Ratio (SNR). The evaluations are performed in different elevation angles from HAPs to user in the ground, velocities of user, and modulation orders. The performance evaluation results of MSE and BER for LMMSE are better than LS, which lower elevation angle has lower performance. Furthermore, higher velocity make increases the performance gap between elevation angles. Finally, higher modulation order also produces lower performance.