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.
Highlights
This section provides an overview of mobile network deployment trends and their holistic planning and optimization frameworks that inspire the research contribution presented .A
WORK We proposed and analyzed a data driven planning framework that considers practical challenges faced in the deployment of a heterogeneous 5G hyperdense network
In the literature review we identified trends and gaps of recent pre-5G and 5G network planning works and noticed that most of the studies employ a greenfield network planning scenario assuming a single radio access technology
Summary
We provide an overview of mobile network deployment trends and their holistic planning and optimization frameworks that inspire the research contribution presented . This contextual information is typically data that provides realistic representation of attributes that influence network planning decision [16] This includes information on the 3D radio propagation environment (buildings, terrain, and other obstacles), spatiotemporal demand distribution (user locations and services consumed), KPI requirements for different services, availability of support infrastructure (site facilities, backhauling, energy sources etc.) and techno-economic parameters (e.g. TCO, average revenue per user, market share etc.). The placement of the core network’s user plane function (UPF) within or on the edge of the RAN is key enabler for provisioning slices with stringent latency requirements [33] These heterogeneous aspects of the 5G-RAN impact network planning not just in terms interworking between systems and implications of different architectures, in a brownfield network planning process that targets to optimize 5G new deployments as complement to legacy pre-5G infrastructure. The vector containing the users’ SINRs (per resource block) is computed using the formula
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
