Analytical Evaluation of Cellular Network Uplink Communications With Higher Order Sectorization Deployments

Higher Order Sectorization (HOS), which splits macro base stations into a larger number of sectors, is widely considered in the cellular community as a cost-effective means of improving network capacity. We develop two general and low-complexity analytical models to characterize and relate the uplink performance indicators with key dynamic functionalities and variables, such as fractional power control (FPC), directional antenna radiation patterns and the multi-cell inter-cell interference (ICI). The adopted methodology approximates the uplink ICIs from individual cell sectors by log-normal random variables, of which the statistical parameters can be estimated using approaches that trade-off complexity and accuracy. Furthermore, the aggregate uplink ICI is approximated with a log-normal random variable, from which network performance metrics are computed. Compared to two existing baseline analytical methods the proposed analytical models have improved accuracy. The analytical models are applied to evaluate HOS deployments with both regular and irregular cell geometries. Results on sectorization scaling show it is an effective method in capacity scaling, but at the cost of increased outage probability. The proposed theoretical models can be used as a fast and effective tool for performance assessment and optimization of Long-Term Evolution (LTE) and 5G networks.