Dynamic optimization in future cellular networks

Abstract

With multiple air-interface support capabilities and higher cell densities, future cellular networks will offer a diverse spectrum of user services. The resulting dynamics in traffic load and resource demand will challenge present control loop algorithms. In addition, frequent upgrades in the network infrastructure will substantially increase the network operation costs if done using current optimization methodology. This motivates the development of dynamic control algorithms that can automatically adjust the network to changes in both traffic and network conditions and autonomously adapt when new cells are added to the system. Bell Labs is pursuing efforts to realize such algorithms with research on near-term approaches that benefit present third-generation (3G) systems and the development of control features for future networks that perform dynamic parameter adjustment across protocol layers. In this paper, we describe the development of conceptual approaches, algorithms, modeling, simulation, and real-time measurements that provide the foundation for future dynamic network optimization techniques.