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.

Architecture and protocols for LTE-based device to device communication

Abstract: The evolution of cellular wireless communications has involved the introduction of technologies such as multiple antennas, OFDM, higher spectral efficiency through better modulation, denser deployments and carrier aggregation. A different approach to enhancing the cellular network by using direct communication between UEs is presented in this paper. Direct device-to-device (D2D) communication can be used for several purposes including network traffic offloading, public safety, and social applications such as gaming. The architectural and protocol enhancements required to extend the current 3GPP LTE-Advanced system to incorporate D2D communication are described, including the logical functions of a D2D server in the core network, the procedures for devices to discover each other and obtain D2D services, the steps involved in establishing and maintaining a D2D call and procedures for efficient mobility between a traditional cellular mode and a D2D mode of operation.

An adaptive bias configuration strategy for range extension in LTE-advanced heterogeneous networks

Abstract: The coexistence of macro eNodeBs and the additional low power nodes (LPNs) may lead to much higher interference in LTE-Advanced Heterogeneous Networks (HetNets) In Macro Pico scenario, Range Extension (RE) is a promising scheme to utilize the LPN resources more effectively and improve the cell edge performance However, it may introduce more interference if the bias value is not properly set In this paper, an adaptive bias configuration strategy for RE is proposed In this strategy, the bias value is set adaptively according to the environment variability, which contains three stages including bias initialization, system performance feedback and dynamic bias value setting The proposed scheme aims to make the RE scheme adaptive and improve the cell edge users' performance through cell load balance Simulation results show that the proposed scheme can improve the cell edge performance compared with the static bias setting strategies, while maintaining the overall cell performance

Vision for Beyond 4G broadband radio systems

Abstract: Mobile communication systems have evolved over the past decades and each new generation brought new experience to the users enabled by technology innovations, while keeping some well established principles from previous generations. This trend continued up to LTE (Long Term Evolution) Advanced, the predominant 4th generation system which has just been standardized in 3GPP and is being rolled out soon. How will this trend continue to future systems which will be deployed in some 10 years from now which will be advanced enough to be called “Beyond 4G” (B4G)? This article presents how such B4G systems will look like and some key technologies they will rely on including versatile numerology, massive virtual MIMO from many base stations, both centralized and distributed architectures using fiber optics as backbone, advanced interference mitigation, cognitive self organization, and wideband RF radios.

Resource allocation with carrier aggregation in LTE Advanced cellular system sharing spectrum with S-band radar

Abstract: Spectrum sharing is a promising solution for the problem of spectrum congestion. We consider a spectrum sharing scenario between a multiple-input multiple-output (MIMO) radar and Long Term Evolution (LTE) Advanced cellular system. In this paper, we consider resource allocation optimization problem with carrier aggregation. The LTE Advanced system has N BS base stations (BS) which it operates in the radar band on a sharing basis. Our objective is to allocate resources from the LTE Advanced carrier and the MIMO radar carrier to each user equipment (UE) in an LTE Advanced cell based on the running application of UE. Each user application is assigned a utility function based on the type of application. We propose a carrier aggregation resource allocation algorithm to allocate the LTE Advanced and the radar carriers' resources optimally among users based on the type of user application. The algorithm gives priority to users running inelastic traffic when allocating resources. Finally we present simulation results on the performance of the proposed carrier aggregation resource allocation algorithm.

Rethinking Mobile Data Offloading for LTE in Unlicensed Spectrum

Abstract: Traditional mobile data offloading transfers cellular users to WiFi networks to relieve the cellular system from the pressure of the ever-increasing data traffic load. However, the spectrum utilization of the WiFi network is bound to suffer from potential packet collisions due to its contention-based access protocol, especially when the number of competing WiFi users grows large. To tackle this problem, we propose transfering some WiFi users to be served by the LTE system, in contrast to the traditional mobile data offloading which effectively offloads LTE traffic to the WiFi network. Meanwhile, leveraging the emerging LTE in unlicensed spectrum (LTE-U) technology, some unlicensed spectrum resources may be allocated to the LTE system in compensation for handling more WiFi users. In this way, a win–win situation would be generated since LTE can generally achieve better performance than WiFi due to its capability of centralized co-ordination. To facilitate it, three important challenging issues are addressed in the paper: which WiFi users should be transferred; how many WiFi users need to be transferred; and how much unlicensed resources should be relinquished to the LTE-U network. We investigate three different user transfer schemes according to the availability of channel state information (CSI): the random transfer, the distance-based transfer, and the CSI-based transfer. In each scheme, the minimum required amount of unlicensed resources under a given transferred user number is analyzed. Furthermore, we utilize the Nash bargaining solution (NBS) to develop joint user transfer and unlicensed resource allocation strategy to fulfill the win–win situation for both networks, whose performance is demonstrated by numerical simulation.