Content-specific broadcast cellular networks based on user demand prediction: A revenue perspective

The Long Term Evolution (LTE) broadcast is a promising solution to cope with exponentially increasing user traffic by broadcasting common user requests over the same frequency channels. In this paper, we propose a novel network framework provisioning broadcast and unicast services simultaneously. For each serving file to users, a cellular base station determines either to broadcast or unicast the file based on user demand prediction examining the file's content specific characteristics such as: file size, delay tolerance, price sensitivity. In a network operator's revenue maximization perspective while not inflicting any user payoff degradation, we jointly optimize resource allocation, pricing, and file scheduling. In accordance with the state of the art LTE specifications, the proposed network demonstrates up to 32% increase in revenue for a single cell and more than a 7-fold increase for a 7 cell coordinated LTE broadcast network, compared to the conventional unicast cellular networks.

[1]  David Gomez-Barquero,et al.  Joint Delivery of Unicast and E-MBMS Services in LTE Networks , 2012, IEEE Transactions on Broadcasting.

[2]  Frederic Gabin,et al.  Evolved multimedia broadcast/multicast service (eMBMS) in LTE-advanced: overview and Rel-11 enhancements , 2012, IEEE Communications Magazine.

[3]  Pablo Rodriguez,et al.  I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system , 2007, IMC '07.

[4]  Seong-Lyun Kim,et al.  Cost-Effective Broadcast in Cellular Networks , 2013, ArXiv.

[5]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.

[6]  Jeffrey G. Andrews,et al.  Seven ways that HetNets are a cellular paradigm shift , 2013, IEEE Communications Magazine.

[7]  Ling Qiu,et al.  QoS-Aware Scheduling and Resource Allocation for Video Streams in e-MBMS Towards LTE-A System , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[8]  Markus Fiedler,et al.  Quality of Experience from user and network perspectives , 2010, Ann. des Télécommunications.

[9]  Sangtae Ha,et al.  Incentivizing time-shifting of data: a survey of time-dependent pricing for internet access , 2012, IEEE Communications Magazine.

[10]  Amiya Nayak,et al.  Channel quality-based AMC and smart scheduling scheme for SVC video transmission in LTE MBSFN networks , 2012, 2012 IEEE International Conference on Communications (ICC).

[11]  Robert G. Gallager,et al.  Discrete Stochastic Processes , 1995 .