Dynamic Demand Control with Differentiated QoS in User-in-the-Loop Controlled Cellular Networks

Cellular communications now and beyond 2020 faces a number of challenges. One of the trends is the ever increasing demand for data rate due to smart mobile devices with an estimated traffic growth of almost 100% per annum. Even with new cellular generation cycles every few years the same increase rate cannot be provided on the supply side. Neither anywhere nor anytime. The gap between supply and demand of wireless capacity will shorten and the conventional over-provisioning approach will not be possible anymore, especially during busy hours. The consequences are more frequent congestion situations with broken application traffic. The quality-of-experience will suffer as user expectations are high and steamed-up by advertising. An inadequate tariff system concentrating on flat-rates is also counterproductive for stability and energy-efficiency. In this paper the temporal user-in-the-loop (UIL) control approach is assumed. This user-centric model implements demand shaping by incentives in form of a dynamic usage-based tariff which adjusts based on the level of congestion in the busy hours. This is comparable to the smart grid operation principle. The novelty in this paper is the differentiated treatment for the exemplary service classes voice, video and data, for which new quantitative user response data is utilized. The control approach performance is calculated and results for stationary and dynamic scenarios are presented.

[1]  Halim Yanikomeroglu,et al.  User in the Loop: Mobility Aware Users Substantially Boost Spectral Efficiency of Cellular OFDMA Systems , 2011, IEEE Communications Letters.

[2]  Deborah Estrin,et al.  Diversity in smartphone usage , 2010, MobiSys '10.

[3]  Halim Yanikomeroglu,et al.  Economics of user-in-the-loop demand control with differentiated QoS in cellular networks , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[4]  Jeffrey K. MacKie-Mason,et al.  Pricing Congestible Network Resources (Invited Paper) , 1995, IEEE J. Sel. Areas Commun..

[5]  Jeffrey K. MacKie-Mason,et al.  A Smart Market for Resource Reservation in a Multiple Quality of Service Information Network , 1997 .

[6]  Jörn Altmann,et al.  How to charge for network services - flat-rate or usage-based? , 2001, Comput. Networks.

[7]  Halim Yanikomeroglu,et al.  Green communications by demand shaping and user-in-the-loop tariff-based control , 2011, 2011 IEEE Online Conference on Green Communications.

[8]  Aurel A. Lazar,et al.  Design and Analysis of the Progressive Second Price Auction for Network Bandwidth Sharing , 1999 .

[9]  John N. Tsitsiklis,et al.  Congestion-dependent pricing of network services , 2000, TNET.

[10]  Halim Yanikomeroglu,et al.  Quantified User Behavior in User-in-the-Loop Spatially and Demand Controlled Cellular Systems , 2012, EW.

[11]  Cem U. Saraydar,et al.  Efficient power control via pricing in wireless data networks , 2002, IEEE Trans. Commun..

[12]  Rainer Schoenen,et al.  On increasing the spectral efficiency more than 100% by user-in-the-control-loop , 2010, 2010 16th Asia-Pacific Conference on Communications (APCC).

[13]  Halim Yanikomeroglu,et al.  On the impact of correlated shadowing on the performance of user-in-the-loop for mobility , 2012, 2012 IEEE International Conference on Communications (ICC).

[14]  Costas Courcoubetis,et al.  A study of simple usage-based charging schemes for broadband networks , 1998 .

[15]  Eitan Altman,et al.  Applications of Dynamic Games in Queues , 2005 .