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On the Performance of RIS-assisted Networks with HQAM

Thrassos K. Oikonomou, Dimitrios Tyrovolas, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Panagiotis Sarigiannidis, Christos Liaskos, George K. Karagiannidis

TL;DR

This work addresses the energy and hardware burden of RIS-assisted networks by evaluating hexagonal QAM (HQAM) modulation. It derives a tight ASEP expression for HQAM in RIS channels through moment-matching of the end-to-end channel, and introduces a conditioned energy efficiency metric $E_c$ that accounts for circuit-level power consumption. A novel $ ext{O}(1)$-complexity HQAM detector leveraging the hexagonal lattice structure is proposed, offering near-ML performance with constant-time complexity. Simulation results show HQAM reduces the required number of RIS elements $N$ and improves both ASEP and energy efficiency compared with QAM, particularly at higher modulation orders, with practical guidance on phase quantization $q$ and detector design for real-world deployments.

Abstract

In this paper, we investigate the application of hexagonal quadrature amplitude modulation (HQAM) in reconfigurable intelligent surface (RIS)-assisted networks, specifically focusing on its efficiency in reducing the number of required reflecting elements. Specifically, we present analytical expressions for the average symbol error probability (ASEP) and propose a new metric for conditioned energy efficiency, which assesses the network energy consumption while ensuring the ASEP remains below a certain threshold. Additionally, we introduce an innovative detection algorithm for HQAM constellations that implements sphere decoding in O(1) complexity. Finally, our study reveals that HQAM significantly enhances both the ASEP and energy efficiency compared to traditional quadrature amplitude modulation (QAM) schemes.

On the Performance of RIS-assisted Networks with HQAM

TL;DR

This work addresses the energy and hardware burden of RIS-assisted networks by evaluating hexagonal QAM (HQAM) modulation. It derives a tight ASEP expression for HQAM in RIS channels through moment-matching of the end-to-end channel, and introduces a conditioned energy efficiency metric that accounts for circuit-level power consumption. A novel -complexity HQAM detector leveraging the hexagonal lattice structure is proposed, offering near-ML performance with constant-time complexity. Simulation results show HQAM reduces the required number of RIS elements and improves both ASEP and energy efficiency compared with QAM, particularly at higher modulation orders, with practical guidance on phase quantization and detector design for real-world deployments.

Abstract

In this paper, we investigate the application of hexagonal quadrature amplitude modulation (HQAM) in reconfigurable intelligent surface (RIS)-assisted networks, specifically focusing on its efficiency in reducing the number of required reflecting elements. Specifically, we present analytical expressions for the average symbol error probability (ASEP) and propose a new metric for conditioned energy efficiency, which assesses the network energy consumption while ensuring the ASEP remains below a certain threshold. Additionally, we introduce an innovative detection algorithm for HQAM constellations that implements sphere decoding in O(1) complexity. Finally, our study reveals that HQAM significantly enhances both the ASEP and energy efficiency compared to traditional quadrature amplitude modulation (QAM) schemes.
Paper Structure (6 sections, 2 theorems, 24 equations, 6 figures, 1 table, 1 algorithm)

This paper contains 6 sections, 2 theorems, 24 equations, 6 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Performance Analysis
  4. Detection Scheme
  5. Numerical Results
  6. Conclusions

Key Result

Proposition 1

The PDF of $\lvert h \rvert$ for the considered RIS-assisted network can be tightly approximated as where $\Gamma(\cdot)$ is the gamma function, $m_{t} = \frac{I_{1}^2 }{I_{2} - I_{1}^2}$, $\Omega_{t} = I_{1}^2$ and $I_1$, $I_2$ are given by eq:I1 and eq:I2 at the top of the next page, respectively.

Figures (6)

  • Figure 1: 64-HQAM constellation
  • Figure 2: Detection scheme of HQAM
  • Figure 3: $M=64$
  • Figure 4: $M=1024$
  • Figure 6: Normalized $E_c$ versus $N$ for $M=1024$
  • ...and 1 more figures

Theorems & Definitions (3)

  • Proposition 1
  • Proposition 2
  • Definition 1