QoE Visualization and Small Cell Planning with Geolocation Algorithm
The data volume dealt in the mobile network has been dramatically increasing due to high video quality applications, IoT devices, social media, etc. MSPs (Mobile Service Providers) needs to accommodate ever growing traffic demands while suppressing OPEX. Consequently the small cell becomes a promising solution meeting MSPs expectation throughout the world. However, the small cell planning is challenging work due to its tremendous numbers to fill in the coverage and capacity but the knowledge of microscopic environments. We have geolocation algorithm driven small cell planning feature in MOON to propose the candidate locations for small cell based on the context aware of end user experience and coverage/capacity situation in street level and per building level.
Small Cell Planning Procedure
The small cells are placed considering RF coverage condition, the traffic absorption, end user experiences (QoE) and especially traffic offloading from macro cell layers.
Dual Layered Geolocation
RF coverage, user throughput and QoE of both indoor and outdoor traffic are presented using dual layer geolocation concept. Dual layered geolocation is possible due to indoor and outdoor traffic discrimination using unsupervised machine learning algorithm.