Handover simulation of LTE and LTE-A standards

Abidi, Khouloud; Hajlaoui, Emna; Abdellaoui, Mahmoud

doi:10.1109/socpar.2014.7007998

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…This issue is typically faced through the usage of network simulators, where many variables or models are artificially generated (e.g., mobility models, interference, packet loss, data burst, weather conditions, and many others). Examples include: [24] and [25], where LTE environments are simulated through NS-2; and [26]- [28], where some LTE metrics are characterized via NS-3. Other works employ customized LTE simulators to model QoE [29], [30] and QoS indicators [32], [33], respectively.…”

Section: Related Work and Offered Contributionmentioning

confidence: 99%

Multivariate Time Series Characterization and Forecasting of VoIP Traffic in Real Mobile Networks

Mauro

Galatro

Postiglione

et al. 2024

IEEE Trans. Netw. Serv. Manage.

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Predicting the behavior of real-time traffic (e.g., VoIP) in mobility scenarios could help the operators to better plan their network infrastructures and to optimize the allocation of resources. Accordingly, in this work the authors propose a forecasting analysis of crucial QoS/QoE descriptors (some of which neglected in the technical literature) of VoIP traffic in a real mobile environment. The problem is formulated in terms of a multivariate time series analysis. Such a formalization allows to discover and model the temporal relationships among various descriptors and to forecast their behaviors for future periods. Techniques such as Vector Autoregressive models and machine learning (deep-based and tree-based) approaches are employed and compared in terms of performance and time complexity, by reframing the multivariate time series problem into a supervised learning one. Moreover, a series of auxiliary analyses (stationarity, orthogonal impulse responses, etc.) are performed to discover the analytical structure of the time series and to provide deep insights about their relationships. The whole theoretical analysis has an experimental counterpart since a set of trials across a real-world LTE-Advanced environment has been performed to collect, post-process and analyze about 600, 000 voice packets, organized per flow and differentiated per codec.

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Section: Related Work and Offered Contributionmentioning

confidence: 99%

Multivariate Time Series Characterization and Forecasting of VoIP Traffic in Real Mobile Networks

Mauro

Galatro

Postiglione

et al. 2024

IEEE Trans. Netw. Serv. Manage.

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“…Many other works rely on the popular NS-2/NS-3 simulator equipped with LTE modules. Among such works we cite: [11] that proposes a performance evaluation of WebRTC traffic by using a mixed simulated/emulated environment with an LTE customized module; [12] where delay and throughput measures are derived for TCP traffic in an LTE setting; [13] where authors analyze the effect of mobility at high speeds with and without handover procedures; [14] that presents a performance evaluation of a streaming video service based on the Real-Time Messaging Protocol across an LTE domain, and where different QoS parameters have been considered.…”

Section: Related Researchmentioning

confidence: 99%

An Experimental Evaluation and Characterization of VoIP Over an LTE-A Network

Mauro

Liotta

2020

IEEE Trans. Netw. Serv. Manage.

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Mobile telecommunications are converging towards all-IP solutions. This is the case of the Long Term Evolution (LTE) technology that, having no circuit-switched bearer to support voice traffic, needs a dedicated VoIP infrastructure, which often relies on the IP Multimedia Subsystem architecture. Most telecom operators implement LTE-A, an advanced version of LTE often marketed as 4G+, which achieves data rate peaks of 300 Mbps. Yet, although such novel technology boosts the access to advanced multimedia contents and services, telco operators continue to consider the VoIP market as the major revenue for their business. In this work, the authors propose a detailed performance assessment of VoIP traffic by carrying out experimental trials across a real LTE-A environment. The experimental campaign consists of two stages. First, we characterize VoIP calls between fixed and mobile terminals, based on a dataset that includes more than 750,000 data-voice packets. We analyze quality-of-service metrics such as round-trip time (RTT) and jitter, to capture the influence of uncontrolled factors that typically appear in real-world settings. In the second stage, we further consider VoIP flows across a range of codecs, looking at the trade-offs between quality and bandwidth consumption. Moreover, we propose a statistical characterization of jitter and RTT (representing the most critical parameters), identifying the optimal approximating distribution, namely the Generalized Extreme Value (GEV). The estimation of parameters through the Maximum Likelihood criterion, leads us to reveal both the shortand long-tail behaviour for jitter and RTT, respectively. Index Terms-VoIP performance analysis, Long Term Evolution paradigm, VoIP over Mobile, VoIP traffic characterization. I. INTRODUCTION N OWADAYS, the high demand for low-cost, voice-based communication services has a great impact on the growth of the mobile VoIP (Voice over IP) market. According to a recent Ericsson research [1], VoLTE (Voice over LTE) subscriptions will reach 5.5 billion by the end of 2023. This unprecedented growth is sustained by an ever decreasing cost of internet-based services, including VoIP, and flat-rate packages. However, by contrast to conventional IP services, which operate on a best-effort model, VoIP sessions pose real-time constraints on the network Quality of Service (QoS) metrics, aiming at acceptable levels of user Quality of Experience (QoE). VoIP sessions typically require a one-way latency between the callers of no more than 150 milliseconds, average jitter (that is the delay variation) under 30 msec, and packet loss rates not exceeding 1% [2].

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