Artificial intelligence linear regression model for mobility robustness optimization algorithm in 5G cellular networks

Saad, Sawsan Ali; Shayea, Ibraheem; Sid Ahmed, Nada M.O.

doi:10.1016/j.aej.2024.01.014

Cited by 6 publications

(1 citation statement)

References 65 publications

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“…Modern 5G base stations commonly utilize beamforming technology, which enhances the directional properties of the beams. There are two types of antennas, namely omnidirectional antennas and array antennas [29]. Array antennas come in various forms, such as 4 × 4, 8 × 8, and 16 × 16.…”

Section: G Base Station Antennamentioning

confidence: 99%

Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters

Duan,

Ma,

Bai

et al. 2024

Sensors

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In this manuscript, we present a novel deployment protection method aimed at safeguarding aeronautical radio altimeters (RAs) from interference caused by fifth-generation (5G) telecommunication base stations (BSs). Our methodology involves an integrated interference model for defining prohibited zones and utilizes power control and angle shutoff methods to mitigate interference. First, to ensure reliable protection, we define both horizontal and vertical prohibited zones and investigate their variations to immunize RA against 5G interference. Second, we validate the effectiveness of the model in various operational scenarios, analyzing the influence of factors such as base station types, antenna parameters, flight altitude, and aircraft attitudes to cover a wide range of real-world scenarios. Third, to mitigate interference, we propose and analyze the power control and angle shutoff methods through simulation for the RMa prohibited zone. Our results demonstrate the efficacy of the deployment protection method in safeguarding RAs from 5G interference, providing guidance for interference protection during civil aviation operations and base station deployment near airports.

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Section: G Base Station Antennamentioning

confidence: 99%

Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters

Duan,

Ma,

Bai

et al. 2024

Sensors

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Adaptive handover control parameters over voronoi-based 5G networks

Tashan,

Shayea,

Sheikh

et al. 2024

Engineering Science and Technology, an International Journal

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Optimal Handover Optimization in Future Mobile Heterogeneous Network Using Integrated Weighted and Fuzzy Logic Models

Tashan,

Shayea,

Aldirmaz-Colak

et al. 2024

IEEE Access

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High mobility travelling trains and drones connected via ultra-dense mobile networks may lead to frequent handovers (HOs). As a consequence, this could arise the mobility problems of the serving network such as handover ping-pong (HOPP), radio link failure (RLF), handover probability (HOP), and handover failure (HOF). Mobility robustness optimization (MRO) function can contribute for fixing such related problems. This can be performed by self-optimization process for the handover control parameters (HCPs), that including time-to-trigger (TTT) and handover margin (HOM). Although various proposed solutions available in the literature, the issues have not been addressed efficiently. Thus, this study proposes a fuzzy logic controller (FLC) along with weighted function (WF) to perform efficient HO self-optimization process for the HCPs over the heterogeneous networks (Het-Nets). The proposed algorithm is defined as velocity-aware-fuzzy logic controller-weighted function (VAW-FLC-WF) algorithm. Additionally, a trigger timer is used along with the proposed algorithm for the purpose of reducing the ratio of HOPP. The objective of the integrated algorithms is to minimize the connections issues such as HOPP, RLF, and received signal reference power (RSRP). Besides, this study highlighted the significant of categorizing the speed scenarios in reducing the mobility issues by comparing the results with non-categorized speed scenarios (proposed FLC-WF). The proposed integrated algorithms show a significant enhancements as compared to the algorithms investigated from the literature. The average RLF probability of the proposed (VAW-FLC-WF) was reduced to 0.006 which was the lowest probability compared to the other HO algorithms. Besides, RSRP, HOPP were shown noticeable improvements compared to other HO algorithms.

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Artificial intelligence linear regression model for mobility robustness optimization algorithm in 5G cellular networks

Cited by 6 publications

References 65 publications

Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters

Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters

Adaptive handover control parameters over voronoi-based 5G networks

Optimal Handover Optimization in Future Mobile Heterogeneous Network Using Integrated Weighted and Fuzzy Logic Models

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