BOLSTER: Beyond 5G mObiLe Standalone Tactical nEtwoRk

In recent years, Belgium has faced a series of major national crises, including the Pukkelpop festival storm in 2016, the Wallonia floods in the summer 2021, the hunt for Jurgen Conings in 2021, and the terrorist attacks at Brussels Airport and metro in 2016. While mobile communication infrastructure such as cellular networks (2G/3G/4G/5G) and TETRA are assumed to be universally accessible by Public Protection & Disaster Relief (PPDR) services, the reality during these crises has revealed the inefficiency and unreliability of fixed communication infrastructure in providing vital connectivity for mission-critical services. Various factors contribute to this inadequacy, including damaged or insufficient infrastructure, overloaded network resources, suboptimal coverage, and a lack of reliability and Quality of Service (QoS). Given the paramount importance of communication during operations involving the Belgian Defense, there is a pressing need for a dependable AD HOC communication network that can be relied upon in such critical situations.

Published on

September 15, 2023

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Intent

The BOLSTER project brings together IMEC, a renowned public research institute in mobile and wireless communications, and Citymesh, a dynamic Mobile Network Operator (MNO) and integrator of smart network infrastructures and drone solutions. Their collaboration aims to design and optimize a private mobile standalone tactical network based on a Beyond 5G (B5G) architecture. Integrated into a Land Rover vehicle, this network will enable automated and ad hoc deployment, offering zero-touch commissioning, deployment, and configuration. It will provide reliable communication services in areas lacking trusted or reliable coverage, supporting mission-critical services for responders such as push-to-talk/video, local dynamic maps, teleoperation of crewless vehicles, and interworking with existing fixed terrestrial and non-terrestrial infrastructures.

Integrated into the Land Rover, the designed network architecture will ensure reliable support for multiple services with diverse Quality of Service (QoS) requirements. It can autonomously adapt to changes in the wireless environment, continuously monitoring the wireless spectrum using advanced AI/ML techniques to gather relevant data and statistics. This information, including the characteristics of co-located wireless technologies and channel occupancy, will be utilized by advanced decision-making mechanisms to fine-tune network parameters autonomously. This optimisation process ensures the optimal utilization of wireless resources and effectively meets the QoS requirements of different services.