Hyperlet Signal Processing for 6G: A Feasibility Study on Super-Resolution for Improved 6G Sensing and Efficiency

Important results from the project

The project applied LucentWave’s core Hyperlet Transform (HLT) to 6G radar sensing. In a drone-swarm simulation it beat the best conventional window by about 35% on rotor detection and about 90% on fine motion detail, with about 15 times fewer missed drones. On real 77 GHz radar data (a SAAB sensor) it told a drone from a bird at 99.3% accuracy and recognised unseen drone types 94.5% of the time, beating the published benchmark (90% and 78%). The feasibility (TRL 1 to 2) goals were met.

Expected long term effects

LucentWave’s core Hyperlet Transform extracts more from 6G sensing than the conventional windows at lower computation: up to about 90% more fine motion detail than the best conventional window, in a single pass. It enables low-power, high-resolution sensing on standard 6G hardware for drone detection, healthcare, industry and infrastructure, and supports energy- efficient 6G (SDG 7) and Swedish competitiveness in 6G and ISAC (SDG 9) via a licensable Swedish IP .

Approach and implementation

The project ran in three work packages (management and future planning; 6G ISAC requirements and use cases; system modelling and evaluation), led by LucentWave with Lund University, whose neuroscience spike-sorting expertise fed the 6G radar pipeline design. The schedule was kept and the simulation and the comparison of HLT against the conventional windows proceeded as planned. Hardware was procured near the end to prepare the next phase; hardware testing lies beyond this feasibility study.