Cloud-Based Implementation of an Automatic Coverage Estimation Methodology for Self-Organising Network

UIDB/EEA/50008/2020One of the main concerns of telecommunications operators is related to network coverage. A weak coverage can lead to a performance decrease, not only in the user experience, when using the operators' services, such as multimedia streaming, but also in the overall Quality of Service. This paper presents a novel cloud-based framework of a semi-empirical propagation model that estimates the coverage in a precise way. The novelty of this model is that it is automatically calibrated by using drive test measurements, terrain morphology, buildings in the area, configurations of the network itself and key performance indicators, automatically extracted from the operator's network. Requirements and use cases are presented as motivations for this methodology. The results achieve an accuracy of about 5 dB, allowing operators to obtain accurate neighbour lists, optimise network planning and automate certain actions on the network by enabling the Self-Organising Network concept. The cloud implementation enables a fast and easy integration with other network management and monitoring tools, such as the Metric platform, optimising operators' resource usage recurring to elastic resources on-demand when needed. This implementation was integrated into the Metric platform, which is currently available to be used by several operators.publishersversionpublishe

OPTIMASI COVERAGE PADA JARINGAN SELULER HETEROGEN 3-SEKTOR BERDASARKAN FUNGSI FITNESS ALGORITMA GENETIKA

Kebutuhan otomasi dalam proses penyelesaian optimasi pada jaringan selular heterogen semakin penting ketika jumlah sel atau site mencapai puluhan atau bahkan ratusan. Penelitian ini mengusulkan penggunaan algoritma genetika, di mana model yang digunakan menggunakan operasi yang sederhana (klasik). Penelitian dilakukan dengan memberikan ilustrasi permasalahan yang dibangkitkan secara acak untuk 135 sel dengan menggunakan basis distribusi hexagonal. Kemudian algoritma GA dibangun dengan menggunakan model-model operasi biasa untuk mengolah data azimuth yang telah diberikan untuk mendapatkan kondisi minimum interferensi. Hasil penelitian memberikan fakta bahwa capaian GA tersebut dapat mencegah interferensi antar site hingga 87.5% di mana jumlah sample yang digunakan adalah 60 titik berdasarkan distribusi hexagonalnya. Kata kunci: Algoritma Genetika, Coverage, Fungsi Fitness, Seluler, Heterogen 3-sektor