NTT Docomo and US-based network equipment manufacturer Abside Networks signed an agreement to explore next-generation, AI-driven networks using high-altitude platform stations (HAPS), as operators look to extend networks beyond terrestrial infrastructure.

Under the memorandum of understanding (MoU), the pair will collaborate on HAPS system architecture, network control and data utilisation. They will also examine how AI can forecast demand and manage radio beams, capacity, spectrum and interference in stratospheric RAN.

In addition, the partners plan to study the collection and use of data on network quality, operations and stratospheric sensing, as well as potential integration with external applications and service platforms.

The agreement supports NTT Docomo’s broader vision for a “three-dimensional communications infrastructure that integrates AI with non-terrestrial network (NTN) initiatives, including HAPS”. Operating at altitudes of around 20km, HAPS use unmanned platforms to provide wide-area connectivity, including to underserved locations where conventional mobile coverage is difficult or uneconomical, such as mountainous regions and maritime areas.

The Japanese operator explained it aims to integrate terrestrial networks with systems in the stratosphere and space to enable wider-area, higher-capacity services that address mounting connectivity demand as AI usage balloons.

NTT Docomo has been conducting research and demonstrations aimed at delivering HAPS-based communications services, but noted the stratospheric environment requires specialised RAN technologies and equipment.

As a result, Abside is developing radio systems based on large antenna arrays for precise beam control, alongside an AI-driven software platform designed to provide “integrated control of networks across the ground, stratosphere and space”.

The equipment manufacturer also brings experience in stratospheric communications through its work on Google’s Project Loon balloon initiative, alongside development of HAPS equipment, NTN technologies and AI-based network control systems.

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