The quality of experience perspective toward 5G technology

Quality of experience (QoE) is the subjective acceptability of the quality of a telecommunication service perceived by the user. This paper expands the vision to new QoE acceptability for the future 5G networks and analyzes the impact of the main challenges of 5G on QoE. An efficient QoE estimation method tailored for 5G systems is also proposed based on the neural network (NN) approach. Due to their ability to fully learn the causal relationship between network parameters of quality of services (QoS) and the resulting QoE, NN can be suitable to gain QoE self-optimization for 5G. Again, new increasingly smart user devices will be delegated to handle the most burdensome tasks of ensuring user satisfaction.

[1]  Romano Fantacci,et al.  Handset and network quality performance benchmarking for QoE improvement , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[2]  Junyi Li,et al.  Network densification: the dominant theme for wireless evolution into 5G , 2014, IEEE Communications Magazine.

[3]  Javier Lorca,et al.  Towards a QoE-Driven Resource Control in LTE and LTE-A Networks , 2013, J. Comput. Networks Commun..

[4]  F. M. Landstorfer,et al.  Radio network planning with neural networks , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[5]  Peter Schelkens,et al.  Qualinet White Paper on Definitions of Quality of Experience , 2013 .

[6]  Theodore S. Rappaport,et al.  Millimeter Wave Mobile Communications for 5G Cellular: It Will Work! , 2013, IEEE Access.

[7]  Pierre Tirilly,et al.  Evaluating Users' Satisfaction in Packet Networks Using Random Neural Networks , 2006, ICANN.

[8]  Vera Stavroulaki,et al.  5G on the Horizon: Key Challenges for the Radio-Access Network , 2013, IEEE Vehicular Technology Magazine.

[9]  Robert W. Heath,et al.  Five disruptive technology directions for 5G , 2013, IEEE Communications Magazine.

[10]  Adlen Ksentini,et al.  Quality of Experience Measurement Tool for SVC Video Coding , 2011, 2011 IEEE International Conference on Communications (ICC).

[11]  Romano Fantacci,et al.  An optimized neural network for monitoring Key Performance Indicators in HSDPA , 2010, 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.