Table of Contents
Fetching ...

Intelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?

Emil Björnson, Özgecan Özdogan, Erik G. Larsson

TL;DR

It is observed that very high rates and/or large metasurfaces are needed to outperform DF relaying, both in terms of minimizing the total transmit power and maximizing the energy efficiency, which also includes the dissipation in the transceiver hardware.

Abstract

The rate and energy efficiency of wireless channels can be improved by deploying software-controlled metasurfaces to reflect signals from the source to the destination, especially when the direct path is weak. While previous works mainly optimized the reflections, this letter compares the new technology with classic decode-and-forward (DF) relaying. The main observation is that very high rates and/or large metasurfaces are needed to outperform DF relaying, both in terms of minimizing the total transmit power and maximizing the energy efficiency, which also includes the dissipation in the transceiver hardware.

Intelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?

TL;DR

It is observed that very high rates and/or large metasurfaces are needed to outperform DF relaying, both in terms of minimizing the total transmit power and maximizing the energy efficiency, which also includes the dissipation in the transceiver hardware.

Abstract

The rate and energy efficiency of wireless channels can be improved by deploying software-controlled metasurfaces to reflect signals from the source to the destination, especially when the direct path is weak. While previous works mainly optimized the reflections, this letter compares the new technology with classic decode-and-forward (DF) relaying. The main observation is that very high rates and/or large metasurfaces are needed to outperform DF relaying, both in terms of minimizing the total transmit power and maximizing the energy efficiency, which also includes the dissipation in the transceiver hardware.

Paper Structure

This paper contains 10 sections, 6 theorems, 20 equations, 5 figures.

Key Result

Lemma 1

The channel capacity of the IRS-supported network is

Figures (5)

  • Figure 1: Illustration of the two setups considered in this paper.
  • Figure 2: Typical channel gains as a function of the distance, when including the antenna gains $G_{\mathrm{t}}=G_{\mathrm{r}}=5$ dBi.
  • Figure 3: The simulation setup where $d_1$ is a variable.
  • Figure 4: The transmit power needed to achieve the rate $\bar{R}$ in the scenario shown in Fig. \ref{['figureSetup']}, as a function of the distance $d_1$.
  • Figure 5: The energy efficiency as a function of the rate $\bar{R}$.

Theorems & Definitions (7)

  • Lemma 1
  • Lemma 2
  • Remark 1
  • Proposition 1
  • Proposition 2
  • Corollary 1
  • Proposition 3