A Data-Driven Multiobjective Optimization Framework for Hyperdense 5G Network Planning

Abstract

The trials and rollout of the fifth generation (5G) network technologies are gradually intensifying as 5G is positioned as a platform that not only accommodates exploding data traffic but also unlocks a multitude use cases, services and deployment scenarios. However, the need for hyperdense 5G deployments is revealing some of the limitations of planning approaches that hitherto proved adequate for pre-5G systems. The hyperdensification envisioned in 5G networks not only adds complexity to network planning and optimization problems, but underlines need for more realistic data-driven approaches that consider cost, varying demands and other contextual attributes to produce feasible topologies. Furthermore, the quest for network programmability and automation including the 5G radio access network (RAN), as manifested by network slicing technologies and more flexible RAN architectures, are also among other factors that influence planning and optimization frameworks. Collectively, these deployment trends, technological developments and evolving (and diverse) service demands point towards the need for more holistic frameworks. This article proposes a data-driven multiobjective optimization framework for hyperdense 5G network planning with practical case studies used to illustrate added value compared to contemporary network planning and optimization approaches. Comparative results from the case study with real network data reveal potential performance and cost improvements of hyperdense optimized networks produced by the proposed framework due to increased use of contextual data of planning area and focus on objectives that target demand satisfaction.

Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0

“…Haile et al presented a data-driven network-planning framework for outdoor fifthgeneration (5G) network-planning [19]. network-planning for WLAN by maximizing network efficiency is presented by Bosio et al [20].…”

“…Haile et al presented a hybrid framework for outdoor network-planning using different radio access technologies [19]. Compared to this framework, we need a more detailed description of the environment and network-planning results, that is, the distances between clients and APs are in the order of meters, rather than km for an outdoor scenario.…”

“…On the other hand, the framework from [19] used a fixed user service demand to plan the network, whereas our framework does not need this a priori information.…”

Analysis of Wave Propagation Models With Radio Network Planning Using Dual Polarized MIMO Antenna for 5G Base Station Applications

“…Antenna technology also advancing starting from monopoles to present complex massive MIMO antennas [17]. To sustain the demand of network capacity the requirement of new technologies with next level set of standards are needed namely 5G [18]. 3rd generation partnership project (3GPP) also focusing and standardizing the requirements for 5G [19].…”

Data-driven optimal antenna planning for enhanced 4G mobile networks under realistic environment

“…A data driven approach is carried out in [31], however, it does not consider cell edge performance as a performance metric. For micro and Pico cells densification, performance analysis, and optimization taking into account realistic network environment for Addis Ababa use cases are presented in [32]- [36].…”