# Next Generation Terahertz Communications: A Rendezvous of Sensing, Imaging, and Localization

arXiv: https://arxiv.org/abs/1909.10462 · HTML: https://mlsanity.com/paper/1909.10462/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2019.

## Built on by (most cited first, 7 of 7)

- [Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design](https://mlsanity.com/paper/2101.09137/) (2021)
- [Joint Sensing, Communication, and AI: A Trifecta for Resilient THz User Experiences](https://mlsanity.com/paper/2305.00135/) (2023)
- [Indoor Localization Under Limited Measurements: A Cross-Environment Joint Semi-Supervised and Transfer Learning Approach](https://mlsanity.com/paper/2108.02257/) (2021)
- [Signal Processing and Machine Learning Techniques for Terahertz Sensing: An Overview](https://mlsanity.com/paper/2104.06309/) (2021)
- [Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework](https://mlsanity.com/paper/2305.09739/) (2023)
- [An Unsupervised Learning Approach for Spectrum Allocation in Terahertz Communication Systems](https://mlsanity.com/paper/2208.03618/) (2022)
- [Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool](https://mlsanity.com/paper/2309.08844/) (2023)

## Abstract (arXiv)

Terahertz (THz)-band communications are celebrated as a key enabling technology for next-generation wireless systems that promises to integrate a wide range of data-demanding and delay-sensitive applications. Following recent advancements in optical, electronic, and plasmonic transceiver design, integrated, adaptive, and efficient THz systems are no longer far-fetched. In this paper, we present a progressive vision of how the traditional "THz gap" will transform into a "THz rush" over the next few years. We posit that the breakthrough that the THz band will introduce will not be solely driven by achievable high data rates, but more profoundly by the interaction between THz sensing, imaging, and localization applications. We first detail the peculiarities of each of these applications at the THz band. Then, we illustrate how their coalescence results in enhanced environment-aware system performance in beyond-5G use cases. We further discuss the implementation aspects of this merging of applications in the context of shared and dedicated resource allocation, highlighting the role of machine learning.