Self-tuning of Remote Electrical Tilts Based on Call Traces for Coverage and Capacity Optimization in LTE

Adjusting antenna tilts is one of the most powerful techniques to solve coverage and capacity problems in cellular networks. In this paper, a novel self-tuning algorithm for adjusting antenna tilts in a Long-Term Evolution (LTE) system on a cell-by-cell basis is presented. The aim of the algorithm is to improve both network coverage and overall spectral efficiency, while eliminating cell overshooting problems. For this purpose, several new indicators are computed to detect insufficient cell coverage, cell overshooting, and abnormal cell overlapping from information available in connection traces. Algorithm assessment is carried out over a static system-level simulator implementing different real macrocellular scenarios. During the analysis, the proposed algorithm is compared with classical self-tuning algorithms that modify other base station parameters, such as transmission power or antenna tilt. Results show that the proposed algorithm can solve overshooting and overlapping problems more effectively than previous algorithms, regardless of the scenario.