Recently different capacity boosting technologies, <span>including 3D beamforming and expanding operating bandwidth have been investigated and included in the enhanced fourth generation (4G) and fifth-generation standards. For mobile operators to enhance their network performance, applying these advanced technologies is vital. To achieve that, planning and optimization work need to consider the spatiotemporal distribution of users. Although the capacity impact of advanced antenna technologies is investigated well, deployment options to exploit their benefits in a cost-effective manner considering a realistic network environment are seldom reported. This work presents a data driven and multi-objective based optimal vertical beams placement for an enhanced 4G mobile network with the newly introduced C-band. The method is utilized for an area located in Addis Ababa, Ethiopia, taking into account the existing 4G mobile network as a reference configuration. Users are distributed based on the data collected by ethio-telecom network management system. Findings indicate that optimal vertical beams placement achieved for gradual deployment with consideration cell edge and aggregate throughput performances while reducing network cost. While being cost-effective, up to 69.2% and 73.8% cell edge performance gain is achieved at 20 and 30 pareto points relative to an existing macro mobile network.</span>
To accommodate the increasing data rate demand, the fifth-generation (5G) cellular network came up with new technological advancements including massive multiple-input multiple-output (massive MIMO) and hyperdensification which can significantly boost network capacity. On the other hand, the introduction of these technologies along with their heterogeneity brings a challenge in terms of network operators’ need to identify a cost-effective optimal deployment approach which is hardly entertained by the legacy planning and optimization method. Hence, to leverage the core benefits of those technologies in a cost-effective manner, we need a holistic planning framework that takes into account their coverage, capacity and cost impact, and realistic spatiotemporal distribution of users. In this work, we present a data-driven multiobjective optimization planning framework that can be used not only for small cells but also for massive MIMO. The planning framework is illustrated using a 5G planning case study for a service area in Addis Ababa, Ethiopia, considering its realistic network data that is collected from the network management system and different potential identified deployment options. Ray tracing is employed to compute propagation, and users and demands are distributed based on the realistic network data. A two-stage optimization and a joint optimization are applied to identify points that provide optimal network performance. Simulation results reveal that the planning method provides Pareto points for different deployment options that can significantly improve the performance of the existing network while reducing the total network cost.
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