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RIS-Assisted Receive Quadrature Spatial Modulation with Low-Complexity Greedy Detection

Mohamad H. Dinan, Marco Di Renzo, Mark F. Flanagan

TL;DR

This work introduces RIS-RQSM, a scheme that harnesses RIS phase control to realize two independent PAM-based components of a QAM symbol at two receive antennas, achieving $R= \log_2 M + 2\log_2 N_r$ bpcu. The transmitter uses RIS-aided phase design and a PAM amplitude with a one-tap ZF pre-equalizer, enabling a low-complexity greedy detector at the receiver with minimal CSI. Key contributions include a max-min RIS phase optimization to simultaneously boost the real and imaginary components, a tight ABEP upper bound for the GD receiver, and an IQ-constellation design that jointly optimizes symbol placement to emulate ML performance. Numerical results show substantial BER improvements over RIS-SM benchmarks, with the gains increasing with the number of receive antennas, indicating strong practical potential for green, high-capacity 6G networks.

Abstract

In this paper, we propose a novel reconfigurable intelligent surface (RIS)-assisted wireless communication scheme which uses the concept of spatial modulation, namely RIS-assisted receive quadrature spatial modulation (RIS-RQSM). In the proposed RIS-RQSM system, the information bits are conveyed via both the indices of the two selected receive antennas and the conventional in-phase/quadrature (IQ) modulation. We propose a novel methodology to adjust the phase shifts of the RIS elements in order to maximize the signal-to-noise ratio (SNR) and at the same time to construct two separate PAM symbols at the selected receive antennas, as the in-phase and quadrature components of the desired IQ symbol. An energy-based greedy detector (GD) is implemented at the receiver to efficiently detect the received signal with minimal channel state information (CSI) via the use of an appropriately designed one-tap pre-equalizer. We also derive a closed-form upper bound on the average bit error probability (ABEP) of the proposed RIS-RQSM system. Then, we formulate an optimization problem to minimize the ABEP in order to improve the performance of the system, which allows the GD to act as a near-optimal receiver. Extensive numerical results are provided to demonstrate the error rate performance of the system and to compare with that of a prominent benchmark scheme. The results verify the remarkable superiority of the proposed RIS-RQSM system over the benchmark scheme.

RIS-Assisted Receive Quadrature Spatial Modulation with Low-Complexity Greedy Detection

TL;DR

This work introduces RIS-RQSM, a scheme that harnesses RIS phase control to realize two independent PAM-based components of a QAM symbol at two receive antennas, achieving bpcu. The transmitter uses RIS-aided phase design and a PAM amplitude with a one-tap ZF pre-equalizer, enabling a low-complexity greedy detector at the receiver with minimal CSI. Key contributions include a max-min RIS phase optimization to simultaneously boost the real and imaginary components, a tight ABEP upper bound for the GD receiver, and an IQ-constellation design that jointly optimizes symbol placement to emulate ML performance. Numerical results show substantial BER improvements over RIS-SM benchmarks, with the gains increasing with the number of receive antennas, indicating strong practical potential for green, high-capacity 6G networks.

Abstract

In this paper, we propose a novel reconfigurable intelligent surface (RIS)-assisted wireless communication scheme which uses the concept of spatial modulation, namely RIS-assisted receive quadrature spatial modulation (RIS-RQSM). In the proposed RIS-RQSM system, the information bits are conveyed via both the indices of the two selected receive antennas and the conventional in-phase/quadrature (IQ) modulation. We propose a novel methodology to adjust the phase shifts of the RIS elements in order to maximize the signal-to-noise ratio (SNR) and at the same time to construct two separate PAM symbols at the selected receive antennas, as the in-phase and quadrature components of the desired IQ symbol. An energy-based greedy detector (GD) is implemented at the receiver to efficiently detect the received signal with minimal channel state information (CSI) via the use of an appropriately designed one-tap pre-equalizer. We also derive a closed-form upper bound on the average bit error probability (ABEP) of the proposed RIS-RQSM system. Then, we formulate an optimization problem to minimize the ABEP in order to improve the performance of the system, which allows the GD to act as a near-optimal receiver. Extensive numerical results are provided to demonstrate the error rate performance of the system and to compare with that of a prominent benchmark scheme. The results verify the remarkable superiority of the proposed RIS-RQSM system over the benchmark scheme.
Paper Structure (9 sections, 2 theorems, 71 equations, 6 figures, 1 table)

This paper contains 9 sections, 2 theorems, 71 equations, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. RIS-Assisted Receive Quadrature Space-Shift Keying dinan2022ris
  4. RIS-Assisted Receive Quadrature Spatial Modulation
  5. Performance Analysis
  6. IQ Modulation Design
  7. Numerical Results
  8. Conclusion
  9. Proof of Theorem \ref{['thm:ave_Y']}

Key Result

Theorem 1

For large values of $N$, the means $\mathbb{E}\left\{ Y_{R}^{\star}\right\}$ and $\mathbb{E}\left\{ Y_{I}^{\star}\right\}$ can be closely approximated by

Figures (6)

  • Figure 1: A schematic representation of RIS-assisted receive quadrature spatial modulation (RIS-RQSM) system (in RIS-RQSSK system, an RF source with constant energy is used).
  • Figure 2: Normalized PAM constellation design for the RIS-RQSM system.
  • Figure 3: Analytical and simulation BER results of the proposed RIS-RQSM system with and without optimized constellation. Here $M=16$, $N=256$, and (a) $N_{r}=4$ ($R=8$ bpcu), (b) $N_{r}=8$ ($R=10$ bpcu).
  • Figure 4: Analytical and simulation BER results of the proposed RIS-RQSM system with and without optimized constellation. Here $M=64$, $N=256$, and (a) $N_{r}=4$ ($R=10$ bpcu), (b) $N_{r}=8$ ($R=12$ bpcu).
  • Figure 5: Comparison of the BER performance of the proposed RIS-RQSM system with that of RIS-SM system for $N=256$, $N_{r}=4$, and (a) $R=8$ bpcu, (b) $R=10$ bpcu.
  • ...and 1 more figures

Theorems & Definitions (2)

  • Theorem 1
  • Theorem 2