Self-Dimensioning and Planning of Small Cell Capacity in Multitenant 5G Networks

TL;DR

This paper introduces an automated framework for planning and managing small cell capacity in multitenant 5G networks, optimizing infrastructure deployment and configuration based on traffic demand data.

Contribution

It presents a novel automated cell planning framework that dynamically adjusts small cell deployment and configuration for multitenant 5G networks using network data.

Findings

Effective planning specifications depend on traffic demand correlation.

The proposed algorithms improve capacity meeting and resource utilization.

Simulation results validate the framework's adaptability and efficiency.

Abstract

An important concept in the fifth generation of mobile networks is multitenancy, which allows diverse operators sharing the same wireless infrastructure. To support this feature in conjunction with the challenging performance requirements of future networks, more automated and faster planning of the required radio capacity is needed. Likewise, installing small cells is an effective resource to provide greater performance and capacity to both indoor and outdoor places. This paper proposes a new framework for automated cell planning in multitenant small cell networks. In particular, taking advantage of the available network data, a set of detailed planning specifications over time and space domains are generated in order to meet the contracted capacity by each tenant. Then, the network infrastructure and configuration are updated according to an algorithm that considers different actions such as adding/removing channels and adding or relocating small cells. The simulation results show the effectiveness of various methods to derive the planning specifications depending on the correlation between the tenant's and network's traffic demands.