QUBYSM - Quantum compUting-enabled Beyond-6G wireless systems via hYper-dimensional Sparse Modulation

• Applicant: Professor Giuseppe Thadeu Freitags de Abreu, Ph.D.
• Subject Area: Communication Technology and Networks, High-Frequency Technology and Photonic Systems, Signal Processing and Machine Learning for Information Technology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 576171458

In spite of a severe spectrum crowding and an increasing concern over excessive energy consumption, a persisting challenge in the evolution of wireless systems has been the ever-greater utilization of resources. For decades, a reliable pathway to improve efficiency in wireless systems has been to employ increasingly sophisticated algorithms, which in turn translates to higher computational capability demands. But although this approach has been so far enabled by Moore’s law, which empirically projects that the density of transistors doubles every two years, it is now widely accepted that the growth of classical computational capacity is expected to flatten soon due to the fundamental physical limitations of conventional transistors, with some forecasting the end of Moore’s law as early as 2030. The predicament is thus clear: with each generation, we have increasing demands, but proportionally less resources and computational capabilities! Time is ripe, therefore, to investigate non-classical approaches to achieve both resource and computational efficiencies, without which progress in the continued evolution of wireless systems will be severely challenged. Fortunately, solutions to this problem also seems to be within reach. On the one hand, resource efficient techniques such as sparse modulation – of which index modulation (IM) is a prominent example – enable information to be conveyed not only through the utilization of resources, but also by choosing, among a large number N of available resources, a smaller number P of resources that are actually activated during signal transmission. And on the other hand, quantum computing (QC) is developing at a fast pace, with room-temperature, commercial quantum computers already available (see quantumcomputinginc.com). The relationship between these approaches is as follows. Conventional IM schemes are typically designed under the assumption that P and N are constant and to apply for a single kind of resource, for instance: carrier IM over frequencies, or spatial IM over transmit antennas. But in order to reach truly significant resource frugality, one must work with a generalized variation of the idea, referred to here as hyper-dimensional sparse modulation (HDSM), in which resources cut across different dimensions (time, frequency, IQ-components, antennas, waveforms, etc.), and in which P and possibly N are not constant. We have shown in previous works that the HSDM concept yields best results P << N, which implies that HDSM has the potential to be extremely resource efficient. However, the generalizations incorporated into the HDSM concept leads to highly complex codebook and receiver designs, which as shown also in some of our preceding work, cannot be handled via classical computers. This is why Project QUBYSM will go beyond conventional approaches and investigate quantum-accelerated mechanisms to design maximum-likelihood-approaching receivers and transmitter (i.e. codebooks) for HDSM schemes.

• DFG Programme: Research Grants