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Network Optimization

Consuming data-intensive Internet services on mobile devices is becoming increasingly popular, and more machines and other artifacts are being connected wirelessly. As a consequence, the amount of mobile data traffic continues to grow massively, thereby elevating the risk of network congestion especially during peak times. This drives the demand to not only expand and optimize mobile access and backhaul transport networks, but also to more intelligently use available resources for delivering the optimal Quality of Experience (QoE) to users.

QoE-aware congestion management and content delivery allows improving users’ mobile service experience while at the same time allowing mobile service providers to generate revenue from both managed and over-the-top services.

Transport Network Resource Optimization helps mobile service providers to intelligently invest in the expansion of their transport network capacity, to lower operational expenditures and to improve the networks' resilience through simplification and automation.

QoE-aware Congestion Management and Content Delivery

Mobile services are not equal. They differ in the way their QoE degrades with increasing levels of network congestion as well as in users’ willingness to pay, and thus the potential to add value for  mobile service providers. This can be exploited during periods of congestion in the radio access or in the core network by applying carefully selected QoE-aware measures of congestion management and content delivery. Our research takes an end-to-end perspective on mobile service delivery and enhances the set of optimization tools available to mobile service providers, e.g. predictive congestion detection and feedback-driven congestion-aware bandwidth control.

Transport Network Resource Optimization

The most effective way of increasing radio access capacity (far more than adding spectrum or improving spectral efficiency) is through shrinking cell sizes. Opportunistic deployment of small cells is ideal for adding spot capacity to a radio access network, but creates new challenges in backhauling vast amounts of mobile data traffic to and from a large number of base stations that may be installed at sites where a wired backhaul infrastructure may not be readily available. Therefore, transport network designers will want to use a mix of different technologies, from optical- or copper-based wireline to micro- or millimeter wave. Our research continuously enhances and improves NEC’s tools and the solutions with which we help our customers to strategically upgrade and optimize the structure of their transport networks (e.g. with our TopoTool) and to manage and operate these networks more efficiently (e.g. through the use of software-defined networking technology).



  • J. Lessmann et al.: Advanced Wireless and optical technologies for small-cell mobile backhaul with dynamic software-defined management. IEEE Communications Magazine SI on Mobile Backhaul for Small Cells, September 2013
  • F. Z. Yousaf, M. Liebsch, A. Maeder, S. Schmid: Mobile CDN Enhancements for QoE-improved Content Delivery in Mobile Operator Networks. IEEE Network Magazine, November 2012.
  • M. Liebsch, S. Schmid and J. Awano: Reducing Backhaul Costs for Mobile Content Delivery – An Analytical Study. In Proc. of IEEE International Conference on Communications (ICC), June 2012, pp. 2895-2900.
  • J. Martin-Hernandez, C. Doerr, J. Lessmann, M. Schoeller: Challenge-Aware traffic protection in wireless mobile backhaul networks. IFIP Networking 2012
  • F. A. Zdarsky, S. Robitzsch, A. Banchs: Security analysis of wireless mesh backhauls for mobile networks. In Journal of Network and Computer Applications, 2011.
  • F.-C. Kuo, F. A. Zdarsky, J. Lessmann, S. Schmid: Cost-Efficient Wireless Mobile Backhaul Topologies: An Analytical Study. In Proc. of IEEE Global Telecommunications Conference (GLOBECOM), 2010, pp. 1-5.
  • J. Lessmann, M. Schoeller, F. Zdarsky: Rope ladder routing: Position-based multipath routing for wireless mesh networks. In Proc. of IEEE International Symposium WoWMoM, 2010.

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