Network optimization trials of a vendor-independent methodology using the Ocelot® tool

Dynamic optimization in future cellular networks

“…The assignment of users to cells is determined by an independent process, which is uncoordinated with channel power allocation and can therefore lead to large variations in power demand from one cell to the next. As shown in numerous predictions and field trials, network capacity can be substantially improved by balancing these load variations through proper reassignment of users from overloaded to lightly loaded cells [5,6,8]. Such a procedure is performed during the network optimization process, where cell boundaries are shifted through adjustments of antenna configuration or pilot power to balance the long-term average loading of cells.…”

“…It also provides the means for a disaggregated solution to the LP that uses local (i.e., cell-level) information to perform part of the processing on a fast time scale and enables definition of a new protocol using intercell communications to balance the load among cells on a slower time scale. The local part of the problem is represented by (5), which resembles the uplink power control problem of CDMA systems and can be handled through an equivalent control algorithm for a given vector of dual variables, . Additionally, (4) and (6) require an algorithm that relies on intercell communications and sets the particular values of .…”

“…Originally, these optimizations were performed through a manual, iterative process relying on network planning tools and drive testing. Bell Labs subsequently introduced the concept of predictive optimization in the Ocelot ® optimization tool, which computes optimum network parameters directly according to well-defined performance metrics [5,7,8]. Its introduction has translated into faster network rollouts, improved network performance, and higher capacity.…”

Novel algorithms for efficient exploration of the tradeoffs between cell count and performance in wireless networks

“…Fast and effective algorithms enable timely interactions with customers and a more complete exploration of the design space. Such algorithms are not merely a luxury; the ability to understand the tradeoffs and to generate high-quality candidate designs can produce significant real-world payoffs [6].…”

“…To this end, Bell Labs has developed the Ocelot ® tool, a sophisticated wireless network simulation and optimization tool that can optimize a cellular network and provide a set of designs that identifies the tradeoff between coverage and capacity [6]. In the past, this tool has been used to optimize the radio and antenna configuration of wireless networks.…”