Hysteresis margin for handover in Long Term Evolution (LTE) network

Yusof, Azita Laily; Ya’acob, Norsuzila; Ali, Mohd Tarmizi

doi:10.1109/commantel.2013.6482433

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…Otherwise, most literature also considers the handover trigger time or strategy with BS and small cell. In [ 12 ], they present the handover flow and trigger condition in the wireless access network. At this network architecture, the eNodeB via the S1 interface connects the mobile management entity (MME), and the interface of X2 will connect the next eNodeB.…”

Section: Methodsmentioning

confidence: 99%

“…In their work, they also consider latency, error rate, and throughput in handover strategies. Following [ 12 , 32 , 33 ], they highlight the key point metrics for designing the handover mechanism to keep the QoS.…”

Section: Methodsmentioning

confidence: 99%

“…There is much literature on the handover strategy for mobile management. Recently, almost all handover trigger mechanisms follow the reference symbol received power ( RSRP ) [ 12 , 13 ] or received signal strength ( RSS ) [ 14 ]. These works also defined the threshold as

and

.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle

Huang

Chen

et al. 2022

Sensors

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With the low latency, high transmission rate, and high reliability provided by the fifth-generation mobile communication network (5G), many applications requiring ultra-low latency and high reliability (uRLLC) have become a hot research topic. Among these issues, the most important is the Internet of Vehicles (IoV). To maintain the safety of vehicle drivers and road conditions, the IoV can transmit through sensors or infrastructure to maintain communication quality and transmission. However, because 5G uses millimeter waves for transmission, a large number of base stations (BS) or lightweight infrastructure will be built in 5G, which will make the overall environment more complex than 4G. The lightweight infrastructure also has to be considered together. For these reasons, in 5G, there are two mechanisms for handover, horizontal, and vertical handover; hence, it must be discussed how to handle handover to obtain the best performance for the whole network. In this paper, to address handover selection, we consider delay time, energy efficiency, load balancing, and energy consumption and formulate it as a multi-objective optimization (MOO) problem. At the same time, we propose the handover of the mobile management mechanism based on location prediction combined with heuristic algorithms. The results show that our proposed mechanism is better than the distance-based one for energy efficiency, load, and latency. It optimizes by more than about 20% at most.

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Section: Methodsmentioning

confidence: 99%