Joint handover decision and channel allocation for LTE-A femtocell networks

Chen, Xin; Wang, Honglu; Xiang, Xudong; Gao, Chaoxin

doi:10.1109/gamenets.2014.7043725

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…The behavior of nodes on the borders is assumed by the rules of the software Bon-nMotion, where nodes that reach the edges of the simulation field will bounce off the border with an angle determined by the incoming direction. These mobility models are selected looking for the development of suitable solutions applicable to current LTE femto-cells mobile networks as described in [42]- [44], and envisaging future 5G and beyond systems. The main features of these entity models are exposed below.…”

Section: Case Of Studymentioning

confidence: 99%

Energy-Efficient Cooperative Spectrum Sensing Based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks

et al. 2021

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Section: Case Of Studymentioning

confidence: 99%

Energy-Efficient Cooperative Spectrum Sensing Based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks

et al. 2021

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“…In Wu, 11 for handover process to function more efficiently, the researchers insisted in their paper on signal strength as one of the major parameters to be considered and suggested a refined handover technique in the LTE/LTE‐A networks. In Chen et al, 12 the researchers focused on handover failure minimization. Introducing a distance algorithm the network is enabled to instruct the MUE to its target FBS for switching.…”

Section: Related Workmentioning

confidence: 99%

Load balancing by diversified quality factors‐based handoff (DQFH) in wireless cellular networks

Riyazuddien

Rao²,

Madhu

2020

Int J Communication

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Summary The long‐term evolution (LTE) and long‐term evolution advance (LTE‐A) communication networks are the buzz of cellular networks. Due to the phenomenal count of users who hangs on cellular networks in regard to the concept of information and communications technology (ICT), the over‐sized demand of any network related to ICT experiences the crux of transmission load, which is critical constraint of the cellular networks. Though the contemporary research evincing the benchmark strategies to deal the crux of load on cellular networks, most of these are adapting handoff schemes to optimize the communication through effective load balancing under one or two standard quality metrics. Hence, the contemporary models have critical droppage in performance under the context of multiple quality objectives. In regard to deprive the constraints of the contemporary models, a handoff mechanism to optimize the load balancing in cellular networks under diversified contextual quality objectives has been defined in this manuscript. The method that is portrayed is a search technique that intends to select an optimal target node. The experimental study that was carried has evinced the significance the proposal that scaled against the contemporary methods having similar objective.

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“…Since the invention of the femtocell was intended to compensate for blind spots and edges in the macrocell base station transmission coverage, it improved the service quality of the network [15]. Hence, we chose a combination model with one macrocell base station and several femtocell base stations.…”

Section: Macro-femtocell Systemmentioning

confidence: 99%

A Novel Base-Station Selection Strategy for Cellular Vehicle-to-Everything (C-V2X) Communications

Hua

Zheng

et al. 2019

Applied Sciences

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Cellular vehicle-to-everything (C-V2X) communication facilitates the improved safety, comfort, and efficiency of vehicles and mobility by exchanging information between vehicles and other entities. In general, only the macrocell or only the femtocell is the communication infrastructure for C-V2X. Currently, a macro-femtocell network is used as the new C-V2X networking architecture. However, there are two unresolved problems for C-V2X in macro-femtocell networks. Firstly, vehicle mobility requires the frequent switching of connections between different base stations; invalid switching results in worse communication quality. Secondly, unintelligent base station selections cause network congestion and network-load imbalance. To address the above challenges, this paper proposes a base station selection strategy based on a Markov decision policy for a vehicle in a macro-femtocell system. Firstly, we present a mechanism to predict received signal strength (RSS) for base station selection. Secondly, a comparing Markov decision policy algorithm is presented in C-V2X. To the best of our knowledge, this is the first attempt to achieve predicted RSS based on a Markov decision policy in C-V2X technology. To validate the proposed mechanism, we simulated the traditional base station selection and our proposal when the vehicle moved at different speeds. This demonstrates that the effectiveness of a traditional base station selection policy is obvious only at high speeds, and this weakness can be resolved by our proposal. Then, we compare our solution with the traditional base station selection policy. The simulation results show that our solution is effective at switching connections between base stations, and it can effectively prevent the overloading of network resources.

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Joint handover decision and channel allocation for LTE-A femtocell networks

Cited by 6 publications

References 16 publications

Energy-Efficient Cooperative Spectrum Sensing Based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks

Energy-Efficient Cooperative Spectrum Sensing Based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks

Load balancing by diversified quality factors‐based handoff (DQFH) in wireless cellular networks

A Novel Base-Station Selection Strategy for Cellular Vehicle-to-Everything (C-V2X) Communications

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