Handover schemes in heterogeneous LTE networks: challenges and opportunities

Li, Yun; Cao, Bin; Wang, Chonggang

doi:10.1109/mwc.2016.7462492

Cited by 73 publications

(43 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors of [24] and [25] study the cell association for renewable energy powered HetNets with backhaul constraints [24] and QoS constraints [25] respectively. The authors of [26] study UE handoff schemes for LTE HetNets.…”

Section: B User Behavior Aware Cell Association Policiesmentioning

confidence: 99%

Cell Association With User Behavior Awareness in Heterogeneous Cellular Networks

Sun

Feng

Qin

et al. 2018

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

In heterogeneous cellular networks (HetNets) with macro base station (MBS) and multiple small BSs (SBSs), cell association of user equipment (UE) affects UE transmission rate and network throughput. Conventional cell association rules are usually based on UE received signal-to-interference-andnoise-ratio (SINR) without being aware of other UE statistical characteristics, such as user movement and distribution. User behaviors can indeed be exploited for improving long term network performance. In this paper, we investigate UE cell association in HetNets by exploiting both individual and clustering user behaviors with aim to maximize long-term system throughput. We model the problem as a stochastic optimization problem, and prove that it is PSPACE-hard. For mathematical tractability, we solve the problem in two steps. In the first step, we investigate UE association for a specific SBS. We use restless multi-armed bandit model to derive association priority index for the SBS. In the second step, we develop an Index Enabled Association (IDEA) policy for making cell association decisions in general HetNets based on the indices derived in the first step. IDEA determines a set of admissible BSs for a UE based on SINR, and then associates the UE with the BS that has the smallest index in the set. We conduct simulation experiments to compare IDEA with other three cell association policies. Numerical results demonstrate the significant advantages of IDEA in typical scenarios.

show abstract

Section: B User Behavior Aware Cell Association Policiesmentioning

confidence: 99%

Cell Association With User Behavior Awareness in Heterogeneous Cellular Networks

Sun

Feng

Qin

et al. 2018

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…The heterogeneous cellular network, which consists of various types of base stations with difference coverage areas, provides a promising solution to meet the ever increasing data traffic demands. 12,13 Instead of deploying macro base stations with high energy consumption and infrastructure cost, low-cost small cells can be deployed densely in the proximity of users to provide high-quality connections. 9 In particular, indoor coverage and network capacity can be dramatically enhanced by the densely deployed small cells as a massive number of concurrent transmission are accommodated simultaneously.…”

Section: Related Workmentioning

confidence: 99%

Optimal pricing strategy for resource allocation in 5G heterogeneous cellular networks

Chen

Liao

et al. 2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Heterogeneous networks provide an effective solution to bridge the gap between enormous global traffic demands and limited spectrum resources. In this paper, we investigate the resource allocation problem in fifth‐generation heterogeneous cellular networks from an economic perspective. We consider the open access scenario where any cellular user equipment is allowed to access either the high‐power node or the low‐power node based on its individual payoff. The resource allocation problem is formulated as a pricing problem, which aims at maximizing the total revenue of the service providers under the user admission constraint. Then, the optimal pricing strategies for both the high‐power node and the low‐power node are developed based on the decisions of cellular user equipments. Simulation results demonstrate that the proposed pricing algorithm can achieve the maximum revenue for service providers under various scenarios.

show abstract

“…Vehicles become as intelligent as smart mobile devices which can support various applications and services, such as autonomous driving, augmented reality (AR), virtual reality (VR), and online gaming [1,2]. Particularly, most of these applications are delay-sensitive and computation-intensive, which result in significant challenges of the computational capability and the battery capability of vehicles [3,4]. Moreover, offloading computation tasks and data traffic to a remote centralized cloud is considered as an effective approach for resolving the above challenges by employing abundant computation resources, which could relieve with cellular base stations to offer services to vehicles in the edge of the radio access network.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient offloading decision-making for mobile edge computing in vehicular networks

Huang

Lai

et al. 2020

J Wireless Com Network

View full text Add to dashboard Cite

Driven by the explosion transmission and computation requirement in 5G vehicular networks, mobile edge computing (MEC) attracts more attention than centralized cloud computing. The advantage of MEC is to provide a large amount of computation and storage resources to the edge of networks so as to offload computation-intensive and delay-sensitive applications from vehicle terminals. However, according to the mobility of vehicle terminals and the time varying traffic load, the optimal task offloading decisions is crucial. In this paper, we consider the uplink transmission from vehicles to road side units in the vehicular network. A dynamic task offloading decision for flexible subtasks is proposed to minimize the utility, which includes energy consumption and packet drop rate. Furthermore, a computation resource allocation scheme is introduced to allocate the computation resources of MEC server due to the differences in the computation intensity and the transmission queue of each vehicle. Consequently, a Lyapunov-based dynamic offloading decision algorithm is proposed, which combines the dynamic task offloading decision and computation resource allocation, to minimize the utility function while ensuring the stability of the queue. Finally, simulation results demonstrate that the proposed algorithm could achieve a significant improvement in the utility of vehicular networks compared with comparison algorithms.

show abstract

Handover schemes in heterogeneous LTE networks: challenges and opportunities

Cited by 73 publications

References 13 publications

Cell Association With User Behavior Awareness in Heterogeneous Cellular Networks

Cell Association With User Behavior Awareness in Heterogeneous Cellular Networks

Optimal pricing strategy for resource allocation in 5G heterogeneous cellular networks

Energy-efficient offloading decision-making for mobile edge computing in vehicular networks

Contact Info

Product

Resources

About