A VoLTE traffic classification method in LTE network

Hyun, Jonghwan; Li, Jian; Im, Chaetae; Yoo, Jae‐Hyoung; Hong, James Won‐Ki

doi:10.1109/apnoms.2014.6996582

Cited by 12 publications

(12 citation statements)

References 4 publications

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“…Since LTE network is a full packet-switched, thus, the deployment of VoLTE service is very complicated. All voice traffics over LTE network are VoIP (Voice over IP) [6]. Also according to [6], there are two types of voice traffic over LTE network, those are VoLTE and VoIP.…”

Section: Introductionmentioning

confidence: 99%

“…All voice traffics over LTE network are VoIP (Voice over IP) [6]. Also according to [6], there are two types of voice traffic over LTE network, those are VoLTE and VoIP. VoLTE is really a VoIP with QoS guaranteed [6].…”

Section: Introductionmentioning

confidence: 99%

“…Also according to [6], there are two types of voice traffic over LTE network, those are VoLTE and VoIP. VoLTE is really a VoIP with QoS guaranteed [6]. However, in order to guarantee VoLTE quality is an extreme challenge.…”

Section: Introductionmentioning

confidence: 99%

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Predicting VoLTE Quality using Random Neural Network

Nguyen¹,

Nguyen²,

Renault³

2016

IJAIS

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Long Term Evolution (LTE) was initially designed for a high data rates network. However, voice service is always a main service that drives huge profits benefit for mobile phone operators. Hence the deployment of Voice over LTE (VoLTE) is very essential. LTE network is a fully All-IP network, thus, the deployment of VoLTE is quite complex, specially for guaranteeing of Quality of Service (QoS) for meeting quality of experience of mobile users. The key purpose of this paper is to present an object, non-intrusive prediction model for VoLTE quality based on Random Neural Network (RNN). In order to simulate an experiment, a three-layer feedforward RNN architecture with gradient descent training algorithm is applied. The inputs of this model are object network impairments such as Packet Loss Rate (PLR), Delay and Jitter. The VoLTE quality was predicted in term of the Mean Opinion Score (MOS). The simulation results show that this model offers MOS values which are quite close to well-known method is WB-PESQ (Wideband Perceptual Evaluation of Speech Quality) model. The results also show that the proposed model is very suitable for predicting voice quality over LTE network.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predicting VoLTE Quality using Random Neural Network

Nguyen¹,

Nguyen²,

Renault³

2016

IJAIS

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“…All voice traffics over LTE network are VoIP (Voice over Internet Protocol) including VoLTE. According to [12], there are two types of voice traffic over LTE network, those are VoLTE and VoIP. VoLTE is really the VoIP service with QoS guaranteed [12].…”

Section: Introductionmentioning

confidence: 99%

“…According to [12], there are two types of voice traffic over LTE network, those are VoLTE and VoIP. VoLTE is really the VoIP service with QoS guaranteed [12]. Table 1 represents the service classes in LTE network where voice service is a Guaranteed Bit Rate (GRB) service which has the second priority just after IP Multimedia Subsystem (IMS) signaling.…”

Section: Introductionmentioning

confidence: 99%

A New Non-intrusive Model for Measuring VoLTE Quality based on Wideband E-model

Nguyen¹,

Nguyen²,

Renault³

2016

CAE

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Long Term Evolution (LTE) was initially designed for a high data rates network. However, voice service is always a main service that brings a big benefit for mobile operators. Hence the deployment of Voice over LTE (VoLTE) is very essential and urgent. LTE network is a fully All-IP network, thus, the deployment of VoLTE is very complex, specially for guaranteeing of Quality of Service (QoS) to meet quality of experience of mobile users. The key purpose of this paper is to present an object, nonintrusive prediction model for VoLTE quality based on LTE-Sim framework and Wideband (WB) E-model. In order to simulate the experiment, we deployed LTE-Sim framework combining C programming in Matlab software. The outputs of the LTE-Sim will be the inputs of the WB E-model. The output of the WB E-model is user satisfaction via Mean Opinion Score (MOS). In addition, due to voice over LTE network (VoLTE) uses Adaptive Multi-Rate Wideband (AMR-WB) for vocoder while LTE-Sim supports only G.729 codec for narrow band, thus, we propose to add AMR-WB codec into LTE-Sim software. The simulation results show that the proposed model can predict voice quality in LTE network via the WB E-model. The proposed model does not refer to the original signal, thus, it is very suitable for predicting voice quality in LTE network for many different scenarios which are configured in the LTE-Sim framework. The proposed model is very suitable for predicting VoLTE quality for transmission planning, and for researchers in Laboratory.

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A robust packet‐dropping covert channel for mobile intelligent terminals

Jun-li

et al. 2022

Int J of Intelligent Sys

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Covert communication in this regard has been widely used for protecting the secrecy of communication.Voice over Long Term Evolution (VoLTE) is a packetswitched core network solution for high-speed and high-quality end-to-end services which usually applied to the communication between intelligent systems. However, covert channels using inter-packet delays and packet order in VoLTE services are limited by specific rules. Since minor modifications to overt traffic can be detected, existing covert channel solutions cannot be directly applied to VoLTE. Therefore, this study presents a robust packet loss covert timing channel by cascade hash coding with intelligent system. To ensure robustness and undetectability, we design hash-based inter-codeword verification, codeword self-verification based on cyclic redundancy check, and adaptive mapping matrix. The sender modulates the covert messages according to the sequence number of the actively dropped packets, and the receiver can retrieve the covert messages using a specialized verification method. To evaluate undetectability, robustness, throughput, and construction costs, a large number of experiments in mobile intelligent terminals have been conducted. The experimental results prove that the proposed scheme is feasible for VoLTE communication, as the covert message is

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A VoLTE traffic classification method in LTE network

Cited by 12 publications

References 4 publications

Predicting VoLTE Quality using Random Neural Network

Predicting VoLTE Quality using Random Neural Network

A New Non-intrusive Model for Measuring VoLTE Quality based on Wideband E-model

A robust packet‐dropping covert channel for mobile intelligent terminals

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