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Reconfigurable Intelligent Surfaces for THz: Hardware Design and Signal Processing Challenges

George C. Alexandropoulos, Antonio Clemente, Sérgio Matos, Ryan Husbands, Sean Ahearne, Qi Luo, Verónica Lain-Rubio, Thomas Kürner, Luís M. Pessoa

TL;DR

Some of the most significant hardware design and signal processing challenges with THz RISs are overviewed, and a preliminary analysis of their impact on the overall link budget and system performance is presented, conducted in the framework of the ongoing TERRAMETA project.

Abstract

Wireless communications in the THz frequency band is an envisioned revolutionary technology for sixth Generation (6G) networks. However, such frequencies impose certain coverage and device design challenges that need to be efficiently overcome. To this end, the development of cost- and energy-efficient approaches for scaling these networks to realistic scenarios constitute a necessity. Among the recent research trends contributing to these objectives belongs the technology of Reconfigurable Intelligent Surfaces (RISs). In fact, several high-level descriptions of THz systems based on RISs have been populating the literature. Nevertheless, hardware implementations of those systems are still very scarce, and not at the scale intended for most envisioned THz scenarios. In this paper, we overview some of the most significant hardware design and signal processing challenges with THz RISs, and present a preliminary analysis of their impact on the overall link budget and system performance, conducted in the framework of the ongoing TERRAMETA project.

Reconfigurable Intelligent Surfaces for THz: Hardware Design and Signal Processing Challenges

TL;DR

Some of the most significant hardware design and signal processing challenges with THz RISs are overviewed, and a preliminary analysis of their impact on the overall link budget and system performance is presented, conducted in the framework of the ongoing TERRAMETA project.

Abstract

Wireless communications in the THz frequency band is an envisioned revolutionary technology for sixth Generation (6G) networks. However, such frequencies impose certain coverage and device design challenges that need to be efficiently overcome. To this end, the development of cost- and energy-efficient approaches for scaling these networks to realistic scenarios constitute a necessity. Among the recent research trends contributing to these objectives belongs the technology of Reconfigurable Intelligent Surfaces (RISs). In fact, several high-level descriptions of THz systems based on RISs have been populating the literature. Nevertheless, hardware implementations of those systems are still very scarce, and not at the scale intended for most envisioned THz scenarios. In this paper, we overview some of the most significant hardware design and signal processing challenges with THz RISs, and present a preliminary analysis of their impact on the overall link budget and system performance, conducted in the framework of the ongoing TERRAMETA project.
Paper Structure (9 sections, 2 equations, 7 figures)

This paper contains 9 sections, 2 equations, 7 figures.

Table of Contents

  1. Introduction
  2. RIS-Enabled THz Use Cases
  3. Outdoor Use Case: Enhancing Coverage to Black Spots
  4. Indoor Use Case: Ensuring High-Speed Connectivity for Industry 4.0 and Beyond
  5. An RIS Design Example at THz
  6. Challenges in THz RIS Design and Operation
  7. Hardware Design
  8. Signal Processing
  9. Conclusion

Figures (7)

  • Figure 1: Non-light of sight communications enabled by an RIS. An example response of a realistic RIS unit cell with $2$-bit amplitude and phase quantization is also illustrated.
  • Figure 2: Reconfigurable technologies for implementing RISs versus the operating frequency.
  • Figure 3: $R_{\rm on}$ and $C_{\rm off}$ performance of reconfigurable technologies for implementing RISs (including publication DOIs) with respect to the maximum handling power and the switching time.
  • Figure 4: Available transmit power levels by a THz source as a function of the operating frequency, considering different technologies for key components of the transmitter (THz gap) THz_Huawei.
  • Figure 5: Output transmit power at $285$ GHz using ACST's Schottky-based sub-THz power sources 9895924.
  • ...and 2 more figures