A statistical comparative performance analysis of mobile network operators

Yildirim, Ahmet; Zeydan, Engin; Yigit, Ibrahim Onuralp

doi:10.1007/s11276-018-1837-6

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Although there have been many works on ensuring reliability aspects for MNOs, no experimental evaluations have been devised for comparisons of different MNOs in terms of their composite metrics such as reliability using a crowdsourced dataset. In our previous related work, we investigated the performance of three MNOs in terms of latency, DL/Upload (UL) speed, jitter, and PL [26]. Different from our previous analysis, in the present paper we extend these comparison ideas into combining different metrics to evaluate the performance of MNOs in terms of their reliability.…”

Section: Reliabilitymentioning

confidence: 99%

Reliability comparisons of mobile network operators: an experimental case study from a crowdsourced dataset

Zeydan¹,

Yıldırım²

2020

Turk J Elec Eng & Comp Sci

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It is of great interest for Mobile Network Operators (MNOs) to know how well their network infrastructure performance behaves in different geographical regions of their operating country compared to their horizontal competitors. However, traditional network monitoring and measurement methods of network infrastructure use limited numbers of measurement points that are insufficient for detailed analysis and expensive to scale using an internal workforce. On the other hand, the abundance of crowdsourced content can engender various unforeseen opportunities for MNOs to cope with this scaling problem. This paper investigates end-to-end reliability and packet loss (PL) performance comparisons of MNOs using a previously collected real-world proprietary crowdsourced dataset from a user application for 13 months' duration in Turkey. More particularly, a unified crowdsourced data-aided statistical MNO comparison framework is proposed, which consists of data collection and network performance analysis steps. Our results are statistically supported using confidence interval analysis for the mean difference of PL ratios and reliability levels of MNOs using unpaired number of observations statistical analysis. The network performance results indicate that significant performance differences in MNOs depending on different regions of the country exist. Moreover, we observe that the overall comparative ordered list of MNOs' reliability performance does not differ when both PL and latency requirements vary.

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Section: Reliabilitymentioning

confidence: 99%

Reliability comparisons of mobile network operators: an experimental case study from a crowdsourced dataset

Zeydan¹,

Yıldırım²

2020

Turk J Elec Eng & Comp Sci

Self Cite

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“…Assuming that the security model is as follows: the web server and the mobile terminal are exposed in the open wireless mobile network environment, and the two must ensure the interaction security and achieve the purpose of authentication when communicating. The authentication server and the web server are deployed in the private cloud environment, and it is considered that the web server and the authentication server have been authenticated [24][25][26]. This solution only needs to focus on ensuring the security of data transmission between the web server and the authentication server.…”

Section: Dual-server Authentication Scheme For Mobile Cloudmentioning

confidence: 99%

A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing

Wang

2022

Wireless Communications and Mobile Computing

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In order to improve the communication security of wireless mobile network, a collaborative intrusion detection method based on cloud computing is studied. The mobile terminal and the cloud computing platform are connected by the wireless mobile network. The cloud computing platform authentication server adopts a dual server and multifactor authentication scheme for mobile cloud computing to provide authentication services for mobile terminal users. The web server of the cloud computing platform uses the intrusion node detection protocol of the neighbor classification mechanism to provide a communication security protocol for users; Using the HMM algorithm, the intrusion detection module of the computing platform realizes the intrusion detection of wireless mobile network. Finally, using authentication service, security protocol, and intrusion detection module completes the cooperative detection of mobile network intrusion. The experimental results show that this method can realize the cooperative detection of wireless mobile network intrusion, and the detection accuracy is as high as 98%, which ensures the communication security of wireless mobile network.

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“…where B is the available spectrum, D is the average cell density, and SE is the per-cell SE which represents the amount of information transferred per second over a unit bandwidth [34]. [37]).…”

Section: Utilized Metricsmentioning

confidence: 99%

Performance comparisons of FDD MIMO and 2.6 GHz TDD massive MIMO: An experimental analysis

Zeydan

Dedeoglu

Türk³

2021

Physical Communication

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Massive multiple-input multiple-output (MIMO) is considered as a breakthrough technology in 5G and beyond 5G systems. Some of its main advantages are providing high spectral efficiency to many users simultaneously in the same timefrequency blocks, strong directive signals towards short-range areas and little interference leaks. However, while massive MIMO exhibits interesting benefits, it is important to investigate its main gains through real deployment scenarios in an operator's infrastructure. In this paper, we focus on performance comparisons of traditional frequency-division duplex (FDD)-based MIMO and 2.6 GHz Time-division duplex (TDD)-based massive MIMO deployments through

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A statistical comparative performance analysis of mobile network operators

Cited by 5 publications

References 14 publications

Reliability comparisons of mobile network operators: an experimental case study from a crowdsourced dataset

Reliability comparisons of mobile network operators: an experimental case study from a crowdsourced dataset

A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing

Performance comparisons of FDD MIMO and 2.6 GHz TDD massive MIMO: An experimental analysis

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