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Open AccessJournal ArticleDOI

Self-Similarity and modeling of LTE/LTE-A data traffic

TLDR
Modeling of user arrival in live LTE network is performed in this work, which is important since the incoming users are predominantly using data traffic compared to that of traditional voice traffic.
About
This article is published in Measurement.The article was published on 2015-11-01 and is currently open access. It has received 18 citations till now. The article focuses on the topics: LTE Advanced.

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Citations
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Journal ArticleDOI

Performance evaluation of XG-PON based mobile front-haul transport in cloud-RAN architecture

TL;DR: An optimized DBA known as optimized round-robin (optimized-RR) that support front-hauling over XG-PONs is proposed that shows significant improvement in upstream delay and utilization as well as lower packet loss and jitter forFront-haul uplink traffic transmitted via XG -PON in virtualized C-RAN architecture.
Proceedings ArticleDOI

Framework for Anticipatory Self-Protective 5G Environments

TL;DR: A novel framework for proactive self-protection on 5G environments is introduced, the description of an architectural framework able to sustain the rest of the anticipation enablers, the formalization of a knowledge representation and reasoning strategy for active cyber threat mitigation, and a prediction strategy adapted to the difficulties inherent in analyzing events on5G scenarios are introduced.
Journal ArticleDOI

Enabling Dynamically Centralized RAN Architectures in 5G and Beyond

TL;DR: This work shows that a dynamically centralized architecture enables drastic interference reductions even when using a very limited fronthaul network, and provides a framework to decide on the best algorithm based on the trade-off between performance, cost, and adaptation time.
Journal ArticleDOI

Survivability Strategies for Emerging Wireless Networks With Data Mining Techniques: a Case Study With NetLogo and RapidMiner

TL;DR: Big data analytics techniques, such as decision trees for detecting nodes that are likely to fail, and so avoid them when routing traffic are proposed to improve the survivability and performance of networks.
Proceedings ArticleDOI

On the Stability of RSRP and Variability of Other KPIs in LTE Downlink - An Open Dataset

Abstract: In this paper, we discuss the temporal behavior of several key parameter indicators (KPIs) in LTE downlink (DL) based on multiple long-term static measurement campaigns conducted under various conditions, including rural and urban indoor and outdoor scenarios. We publish part of the measurements as an open dataset. We conclude that the reference signal received power (RSRP) does not show any time-of-day patterns and thus can be modeled as time-invariant for limited periods of time (from several hours to multiple days) followed by occasional anomalies in the form of jumps of several dB. The other KPIs, for example, throughput, exhibit repeated diurnal patterns with significant differences between peak hours (full cell in the afternoon and evening) and off-peak hours (empty cell in the early morning). Even under model idealizations, such KPIs should be thus modeled at least as cyclostationary random processes. We are not aware of any other paper that would provide static LTE DL measurement data covering several weeks and would thus allow the scientific community to study the diurnal patterns without a need to perform own measurements.
References
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Book

Wireless Communications: Principles and Practice

TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Book

Wireless Communications

Journal ArticleDOI

Wide area traffic: the failure of Poisson modeling

TL;DR: It is found that user-initiated TCP session arrivals, such as remote-login and file-transfer, are well-modeled as Poisson processes with fixed hourly rates, but that other connection arrivals deviate considerably from Poisson.
Journal ArticleDOI

Self-similarity in World Wide Web traffic: evidence and possible causes

TL;DR: It is shown that the self-similarity in WWW traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local-area network.
Book

4G: LTE/LTE-Advanced for Mobile Broadband

TL;DR: In this article, the authors focus on LTE with full updates including LTE-Advanced to provide a complete picture of the LTE system, including the physical layer, access procedures, broadcast, relaying, spectrum and RF characteristics, and system performance.
Related Papers (5)
Frequently Asked Questions (5)
Q1. What have the authors contributed in "Self-similarity and modeling of lte / lte-a data traffic by roopesh kumar polaganga presented to the faculty of the graduate school of the university of texas at arlington in partial fulfillment of the requirements for the degree of master of science in electrical engineering the university of texas at arlington" ?

In this paper, the authors present a list of illustrators and illustrators in the field of illustration. 

The mobile wireless communication system has evolved into its 4th generationwith ubiquitous availability assuring higher data rates and reliable communication. 

This work emphasizes the existence of Self-Similarity in LTE and LTE-A data traffic which can facilitate the future research on forecasting data traffic. 

It is important to model and evaluate the incoming user traffic in their current generation of mobile communication systems which dominated data traffic more than the traditional voice traffic. 

634.5 Carrier Aggregation Performance & Benefits .......................................... 654.6 Impact of CA on Protocol layer level .......................................................