On the Performance of Location Management in 5G Network Using RRC Inactive State

Oliveira, Lidiano A. N.; Alencar, Marcelo S.; Lopes, Waslon T. A.; Madeiro, Francisco

doi:10.1109/access.2022.3178383

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…Figure 1 shows the architecture of 5G mobile communications network [1,7]. The access and mobility management function (AMF) manages mobility of subscribers, and it performs mobility management functions through two main functions: location registration and paging.…”

Section: A 5g Mobile Communication Networkmentioning

confidence: 99%

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Mobility Prediction using Artificial Neural Network in Mobile Communication Network

2023

Feb. 2023 European Conferences

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This paper proposes a method of predicting the movement direction between cells of subscribers (UE, user equipment) for efficient mobility management in mobile communication networks. To predict the moving direction of UE, an artificial neural network model is developed by using R programming language, and location registration and paging costs (signaling bits) for each UE collected are used as dependent variables. In addition, the paging scheme considers the method of paging the incoming calls to the UE at once (simultaneous paging) and the method of paging it twice (selective paging). In addition, softmax is used as an activation function, and a weight reduction method is used to prevent overfitting to construct neural network. From the numerical results, it is observed that the total cost in the selective paging is reduced by about 17.2% compared to the simultaneous paging method. And, as a result of evaluating the accuracy of the model using validation dataset, the accuracy is 63.43% in the simultaneous paging, and the prediction accuracy is improved to 82.9% by confirming the UE at the boundary of the tracking area by using the twostep selective paging technique.

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Section: A 5g Mobile Communication Networkmentioning

confidence: 99%

“…To meet the increasing mobile users (user equipment, UEs) in highly dense mobile communication network, location management plays a fundamental role in 5G networks [1,7]. Tracking UE's location requires considerable efforts, and it consists of two tasks: location registration and paging.…”

Section: Introductionmentioning

confidence: 99%

Mobility Prediction using Artificial Neural Network in Mobile Communication Network

2023

Feb. 2023 European Conferences

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Reducing Signaling Overhead in 5G Mobile Network for IoT Device Mobility

Kato,

Sasaki,

Tagami

2024

Lecture Notes on Data Engineering and Communications Technologies

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RETALIN: A Queue Aware Uplink Scheduling Scheme for Reducing Scheduling Signaling Overhead in 5G NR

Gautam,

Tamma

2024

IEEE Access

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Flexible numerology in 5G New Radio (NR) helps to reduce End-to-End (E2E) delay by supporting different slot duration options. But, higher numerologies can increase signaling overhead (in terms of Scheduling Requests (SRs) in uplink (UL)) for applications which are UL heavy in nature; as a consequence, the E2E delay of such applications could be impacted. This sudden increase in SRs in UL happens when the timing of the Constant-Bit-Rate (CBR) UL transmission is not properly aligned with the slot duration of the numerology employed and aggressive emptying of the buffered data at the User Equipments (UEs) by the UL scheduler. In this work, to minimize SRs while meeting the latency requirements of the UL heavy applications like vehicular applications, we propose a novel UL MAC scheduling algorithm named RETALIN. The proposed RETALIN is a queue-aware radio resource scheduler that estimates the probability of SR with respect to each UE (vehicle) and anatomizes the transient queue behavior by controlling backlogs of the UEs in order to reduce SRs and thereby mitigating an adverse impact of numerology in the UL traffic while keeping a bound on E2E delay of the vehicular applications. Extensive NS-3 simulations are performed to evaluate the performance of the proposed RETALIN scheme with mobility traces taken from Simulation of Urban Mobility (SUMO) using OpenStreetMap. Simulation results show that the proposed RETALIN scheduling scheme significantly reduces link delay for different numerologies when compared with a state-of-art QoS scheduler. Further, RETALIN increases Packet Delivery Ratio (PDR) while reducing signaling overhead due to SRs for UL scheduling. In the case of a High Definition Map (HD Map) vehicular application, RETALIN assists in increasing the Offloading Success Rate (OSR) over the QoS scheduler.INDEX TERMS 5G New Radio (NR), Vehicle to Everything (V2X), Network Simulator 3 (NS-3), Numerology, Radio Resource Management, Uplink scheduling.

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On the Performance of Location Management in 5G Network Using RRC Inactive State

Cited by 4 publications

References 33 publications

Mobility Prediction using Artificial Neural Network in Mobile Communication Network

Mobility Prediction using Artificial Neural Network in Mobile Communication Network

Reducing Signaling Overhead in 5G Mobile Network for IoT Device Mobility

RETALIN: A Queue Aware Uplink Scheduling Scheme for Reducing Scheduling Signaling Overhead in 5G NR

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