Swisscom Ag

Damiano Scanferla

Pavle Belanovic

Methods and systems are provided for data-driven network roll-out planning. Network data associated with a network that includes a plurality of cells may be analyzed, with the analyzing including assessing throughput of users on a sector-by-sector basis in the network. Prioritization information on per-sector basis for the network may be generated, and based on the prioritization information, a network roll-out plan for use in the network may be optimized. The prioritization information may be generated based on a valuation scheme and/or a congestion level. Cost optimization information, for use in the optimizing of the network roll-out plan, may be generated. One or more actions may be recommended based on the network data.

Methods and systems for data-driven roll-out planning optimization

Methods and systems are provided for data-driven network roll-out planning. A network that includes a plurality of cells may be managed, with the managing includes obtaining network data associated with the network; analyzing the network data, with the analyzing including analyzing throughput of users on a sector-by-sector basis in the network; applying, based on the analyzing of the network data, a growth prediction for the network; and optimizing, based on the applying of the growth prediction, a network roll-out plan for use in the network.

Methods and systems are provided for data-driven network roll-out planning. A mobile network that includes at least one sector with a plurality of cells may be rolled-out using carrier aggregation. The carrier aggregation based rolling out includes gathering data from a plurality of network counters associated with two or more cells of the at least one sector; detecting a network congestion situation (Cs), based on a minimal throughput level and an aggregate cumulative distribution function (CDF), where the aggregate CDF is based on the plurality of network counters; identifying one or more cells effecting the congestion situation among the two or more cells; and determining for each of the identified one or more cells whether a capacity or coverage pain point is associated with the congestion situation.

Methods and systems are provided for data-driven roll-out planning optimization. A network roll-out plan, for a network that includes a plurality of cells, may be generated by assessing at least one carrier aggregation (CA) scenario for a particular sector in the network, between two or more cells of the plurality of cells; detecting for the carrier aggregation (CA) scenario, a congestion situation based on probabilities of one or more possible cell connection configurations in the sector, and a predefined minimal throughput level; and assessing achievable data throughput for users in the sector. Cells within a sector where congestion primarily may occur may be identified, based on obtained data associated with the network. The identifying may include comparing at least one ratio of contribution between cells with a balancing ratio. It may be determined whether an identified cell is primarily affected by a coverage or a capacity issue.

Methods and systems are provided for data-driven roll-out planning optimization. An optimized network roll-out plan may be determined for a mobile network comprising sectors fitted with multiple cells operating over respective carrier frequencies by gathering data from several network counters, and analyzing the data to derive the network roll-out plan. Analyzing the data comprises applying congestion detection based on a probability mass function (PMF) and cumulative distribution function (CDF) modelling; and assessing based on the congestion detection achievable data throughput for users in a particular sector. The congestion detection comprises assessing at least one carrier aggregation (CA) scenario for the particular sector, between two or more cells providing coverage in the sector; and detecting for the at least one carrier aggregation (CA) scenario, a congestion situation based on predefined percentile of an aggregated CDF curve weighted based on probabilities of possible cell connection configurations, and a predefined minimal throughput level.

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Bern, Switzerland

Damiano Scanferla