Performance Evaluation of End-to-End Communication Quality of LTE

Zhang, Liang; Okamawari, Takao; Fujii, Teruya

doi:10.1109/vetecs.2012.6240243

Cited by 10 publications

(7 citation statements)

References 2 publications

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“…This kind of analysis can be carried out by means of field trials [22][23][24] or by using call traces (or MDT) [25]. However, in the case of field trials, the conclusions may not be representative of the real QoS experienced by the users.…”

Section: Related Workmentioning

confidence: 99%

A method for identifying faulty cells using a classification tree-based UE diagnosis in LTE

Muñoz

Barco

Cruz

et al. 2017

J Wireless Com Network

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The latest advances in wireless technologies have led to a proliferation of data mobile devices and services. As a consequence, mobile networks have experienced a significant increase in data traffic, while voice traffic has shown nearly no growth. It is therefore essential for operators to understand the data traffic behavior at the user level in order to ensure a good customer experience. In the radio access networks (RANs), traditional solutions based on cell-level measurements are not adequate to analyze performance of individual users. Instead, novel alternatives such as the use of call traces and the definition of new user-centric indicators will provide detailed and valuable information for each connection. One of the key measurements related to data services is the user throughput. In this work, the user throughput is adopted as the main attribute to conduct diagnosis in the RAN, which has typically been the bottleneck for data services. To that end, a binary classification tree is proposed to determine the root cause of poor throughput in user-level data sessions. Then, this information is aggregated at the cell level in order to provide effective diagnosis of degraded cells. In particular, a correlation-based analysis of the cell status is proposed in order to identify abnormal cell behaviors in an automatic way. Evaluation has been carried out with datasets from live cellular networks. Results show that the proposed diagnosis approach is an effective means to identify the main factors that limit the user throughput in network cells.

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Section: Related Workmentioning

confidence: 99%

A method for identifying faulty cells using a classification tree-based UE diagnosis in LTE

Muñoz

Barco

Cruz

et al. 2017

J Wireless Com Network

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“…In this document, we consider the Sync HARQ. The maximal retransmission number for a message is 3 times, i.e there are 4 packets (including an original packet) resent at maximum for a message sent by the train or the ZC [14], [7].…”

Section: A Problem Statementmentioning

confidence: 99%

“…The other parameters are given in the Table I TABLE I INPUT PARAMETERS FOR THE CASE STUDY Connection loss λ l p f 2.78E-7/s (1) 0.001 (2) Note that the input parameters is chosen (1) arbitrarily but try to come close to reality, (2) based on [16], (3) based on [14], (4) based on [7], (5) based on [3], (6) based on [5].…”

Section: B Analysis Of the Case Studymentioning

confidence: 99%

Modelling Communication Based Train Control System for Dependability Analysis of the LTE Communication Network in Train Control Application

Nguyen¹,

Beugin²,

Berbineau³

et al. 2014

2014 European Modelling Symposium

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The Communication Based Train Control (CBTC) systems today has generated immense interest in transport domain because of its ability to enhance safety and improve operational effectiveness. The current communication solutions for urban guided transport system that is based on the Wireless local area network (WLAN) becomes obsolete with a number of shortcomings in term of capacity and capability. Hence, the Long Term Evolution (LTE) is considered as a new solution for railway communication technology. Before widely deploying this new solution in railway industry, it must be evaluated and tested to ensure the desired performance level for CBTC system according to the railway safety standards. Therefore, it is necessary to propose a model of CBTC system that allows to consider the behaviours of the LTE communication network in real time. In this paper, we propose to use Petri nets for modelling CBTC system based on a LTE architecture. Using this model, preliminary dependability analysis for the data communication system based on the LTE technology is then performed.

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“…(The main features are summarized in Table 1.) We measure the transmission delay of the UDP packets by the method introduced in [7]. When UDP packets pass through probe1 and probe2, the time is recorded.…”

Section: Amentioning

confidence: 99%

“…All these issues make it difficult to predict the delay performance of LTE in a realistic radio propagation environment. In our previous work, we measured the end-to-end delay performance of a real LTE system [7]. The measurements showed that the delay distribution depended on the traffic pattern and radio propagation environment.…”

Section: Introductionmentioning

confidence: 99%

Delay Performance Analysis of LTE in Various Traffic Patterns and Radio Propagation Environments

Nagai

Zhang

Okamawari

et al. 2013

2013 IEEE 77th Vehicular Technology Conference (VTC Spring)

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Most real-time multimedia services like VoIP (voice over IP), TV conference and real-time gaming require low endto-end delay. In the near future, it is expected that more delay sensitive applications such as cloud computing or telepresence will appear. LTE (long term evolution) is able to provide realtime services in mobile environments. LTE is designed to have an end-to-end delay of less than 5ms. The delay performance in LTE may, however, be degraded by the radio propagation environment or traffic pattern. For example, if the quality of radio signal is poor, more retransmission is required between eNB (evolved NodeB) and UE (user equipment) which degrades the delay performance. If packet size is large, the packets may be segmented which also degrades the delay performance. Thus it is very difficult to predict the delay performance of LTE system prior to its installation. This paper analyzes how the delay performance in the layer 2 (L2) process of LTE is affected depending on the traffic pattern and radio propagation environment. We conduct numerical simulations that consider the L2 processes. The numerical simulation correctly estimates the delay pattern even in a realistic fading environment.

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Performance Evaluation of End-to-End Communication Quality of LTE

Cited by 10 publications

References 2 publications

A method for identifying faulty cells using a classification tree-based UE diagnosis in LTE

A method for identifying faulty cells using a classification tree-based UE diagnosis in LTE

Modelling Communication Based Train Control System for Dependability Analysis of the LTE Communication Network in Train Control Application

Delay Performance Analysis of LTE in Various Traffic Patterns and Radio Propagation Environments

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